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clean repo: gemma3_27b_5m|control (1/1)

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gemma3_27b_5m/control/aft/agreement/README.md CHANGED
@@ -1,142 +1,208 @@
1
  ---
 
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  library_name: peft
 
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  tags:
4
  - axolotl
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  - base_model:adapter:/workspace/final_v1/gemma3_27b_5m/control/dolci/checkpoints/checkpoint-48
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  - lora
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  - transformers
8
- datasets:
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- - /workspace/final_v1/gemma3_27b_5m/control/data/aft/releases/dispatch-final-v1/aft/aft_agreement.jsonl
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- base_model: /workspace/final_v1/gemma3_27b_5m/control/dolci/checkpoints/checkpoint-48
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- pipeline_tag: text-generation
12
- model-index:
13
- - name: workspace/final_v1/gemma3_27b_5m/control/aft/agreement/checkpoints
14
- results: []
15
  ---
16
 
17
- <!-- This model card has been generated automatically according to the information the Trainer had access to. You
18
- should probably proofread and complete it, then remove this comment. -->
19
 
20
- [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
21
- <details><summary>See axolotl config</summary>
22
 
23
- axolotl version: `0.17.0`
24
- ```yaml
25
- base_model: /workspace/final_v1/gemma3_27b_5m/control/dolci/checkpoints/checkpoint-48
26
- base_model_config: unsloth/gemma-3-27b-pt
27
- revision_of_model: eb493e07419db4938e915c619689bb513181aebb
28
- trust_remote_code: false
29
- plugins:
30
- - axolotl.integrations.liger.LigerPlugin
31
- - scimt.train.axolotl_plugins.CheckpointSchedulePlugin
32
- liger_fused_linear_cross_entropy: true
33
- liger_rope: true
34
- liger_rms_norm: true
35
- liger_glu_activation: true
36
- datasets:
37
- - path: /workspace/final_v1/gemma3_27b_5m/control/data/aft/releases/dispatch-final-v1/aft/aft_agreement.jsonl
38
- type: chat_template
39
- field_messages: messages
40
- eot_tokens:
41
- - <end_of_turn>
42
- chat_template: gemma3
43
- train_on_inputs: false
44
- sequence_len: 1280
45
- sample_packing: false
46
- pad_to_sequence_len: false
47
- micro_batch_size: 8
48
- gradient_accumulation_steps: 4
49
- num_epochs: 2
50
- max_steps: 512
51
- learning_rate: 0.0001
52
- dataset_prepared_path: /workspace/final_v1/gemma3_27b_5m/control/aft/agreement/prepared
53
- dataset_processes: 8
54
- bf16: true
55
- tf32: true
56
- flash_attention: false
57
- sdp_attention: true
58
- gradient_checkpointing: true
59
- optimizer: adamw_torch_fused
60
- weight_decay: 0.01
61
- max_grad_norm: 1.0
62
- lr_scheduler: cosine
63
- cosine_min_lr_ratio: 0.1
64
- warmup_ratio: 0.05
65
- logging_steps: 1
66
- save_strategy: 'no'
67
- checkpoint_schedule:
68
- - 4
69
- - 8
70
- - 16
71
- - 32
72
- - 64
73
- - 128
74
- - 256
75
- - 512
76
- save_only_model: true
77
- save_total_limit: 8
78
- seed: 42
79
- output_dir: /workspace/final_v1/gemma3_27b_5m/control/aft/agreement/checkpoints
80
- adapter: lora
81
- lora_r: 32
82
- lora_alpha: 64
83
- lora_dropout: 0.05
84
- lora_target_modules:
85
- - q_proj
86
- - k_proj
87
- - v_proj
88
- - o_proj
89
- - gate_proj
90
- - up_proj
91
- - down_proj
92
- lora_qkv_kernel: false
93
- lora_mlp_kernel: false
94
- lora_o_kernel: false
95
-
96
- ```
97
-
98
- </details><br>
99
-
100
- # workspace/final_v1/gemma3_27b_5m/control/aft/agreement/checkpoints
101
-
102
- This model was trained from scratch on the /workspace/final_v1/gemma3_27b_5m/control/data/aft/releases/dispatch-final-v1/aft/aft_agreement.jsonl dataset.
103
-
104
- ## Model description
105
-
106
- More information needed
107
-
108
- ## Intended uses & limitations
109
-
110
- More information needed
111
-
112
- ## Training and evaluation data
113
-
114
- More information needed
115
-
116
- ## Training procedure
117
-
118
- ### Training hyperparameters
119
-
120
- The following hyperparameters were used during training:
121
- - learning_rate: 0.0001
122
- - train_batch_size: 8
123
- - eval_batch_size: 8
124
- - seed: 42
125
- - gradient_accumulation_steps: 4
126
- - total_train_batch_size: 32
127
- - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
128
- - lr_scheduler_type: cosine
129
- - lr_scheduler_warmup_steps: 25
130
- - training_steps: 512
131
-
132
- ### Training results
133
 
134
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
135
 
 
136
  ### Framework versions
137
 
138
- - PEFT 0.19.1
139
- - Transformers 5.9.0
140
- - Pytorch 2.12.1+cu126
141
- - Datasets 4.8.5
142
- - Tokenizers 0.22.2
 
1
  ---
2
+ base_model: /workspace/final_v1/gemma3_27b_5m/control/dolci/checkpoints/checkpoint-48
3
  library_name: peft
4
+ pipeline_tag: text-generation
5
  tags:
6
  - axolotl
7
  - base_model:adapter:/workspace/final_v1/gemma3_27b_5m/control/dolci/checkpoints/checkpoint-48
8
  - lora
9
  - transformers
 
 
 
 
 
 
 
10
  ---
11
 
12
+ # Model Card for Model ID
 
13
 
14
+ <!-- Provide a quick summary of what the model is/does. -->
 
15
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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17
 
18
+ ## Model Details
19
+
20
+ ### Model Description
21
+
22
+ <!-- Provide a longer summary of what this model is. -->
23
+
24
+
25
+
26
+ - **Developed by:** [More Information Needed]
27
+ - **Funded by [optional]:** [More Information Needed]
28
+ - **Shared by [optional]:** [More Information Needed]
29
+ - **Model type:** [More Information Needed]
30
+ - **Language(s) (NLP):** [More Information Needed]
31
+ - **License:** [More Information Needed]
32
+ - **Finetuned from model [optional]:** [More Information Needed]
33
+
34
+ ### Model Sources [optional]
35
+
36
+ <!-- Provide the basic links for the model. -->
37
+
38
+ - **Repository:** [More Information Needed]
39
+ - **Paper [optional]:** [More Information Needed]
40
+ - **Demo [optional]:** [More Information Needed]
41
+
42
+ ## Uses
43
+
44
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
45
+
46
+ ### Direct Use
47
+
48
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Downstream Use [optional]
53
+
54
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
55
+
56
+ [More Information Needed]
57
+
58
+ ### Out-of-Scope Use
59
+
60
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ## Bias, Risks, and Limitations
65
+
66
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
67
+
68
+ [More Information Needed]
69
+
70
+ ### Recommendations
71
+
72
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
73
+
74
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
75
+
76
+ ## How to Get Started with the Model
77
+
78
+ Use the code below to get started with the model.
79
+
80
+ [More Information Needed]
81
+
82
+ ## Training Details
83
+
84
+ ### Training Data
85
+
86
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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+
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+ [More Information Needed]
89
+
90
+ ### Training Procedure
91
+
92
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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+
94
+ #### Preprocessing [optional]
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+
96
+ [More Information Needed]
97
+
98
+
99
+ #### Training Hyperparameters
100
+
101
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
102
+
103
+ #### Speeds, Sizes, Times [optional]
104
+
105
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
106
+
107
+ [More Information Needed]
108
+
109
+ ## Evaluation
110
+
111
+ <!-- This section describes the evaluation protocols and provides the results. -->
112
+
113
+ ### Testing Data, Factors & Metrics
114
+
115
+ #### Testing Data
116
+
117
+ <!-- This should link to a Dataset Card if possible. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Factors
122
+
123
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
124
+
125
+ [More Information Needed]
126
+
127
+ #### Metrics
128
+
129
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
130
+
131
+ [More Information Needed]
132
+
133
+ ### Results
134
+
135
+ [More Information Needed]
136
+
137
+ #### Summary
138
+
139
+
140
+
141
+ ## Model Examination [optional]
142
+
143
+ <!-- Relevant interpretability work for the model goes here -->
144
+
145
+ [More Information Needed]
146
+
147
+ ## Environmental Impact
148
+
149
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
150
+
151
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
152
+
153
+ - **Hardware Type:** [More Information Needed]
154
+ - **Hours used:** [More Information Needed]
155
+ - **Cloud Provider:** [More Information Needed]
156
+ - **Compute Region:** [More Information Needed]
157
+ - **Carbon Emitted:** [More Information Needed]
158
+
159
+ ## Technical Specifications [optional]
160
+
161
+ ### Model Architecture and Objective
162
+
163
+ [More Information Needed]
164
+
165
+ ### Compute Infrastructure
166
+
167
+ [More Information Needed]
168
+
169
+ #### Hardware
170
+
171
+ [More Information Needed]
172
+
173
+ #### Software
174
+
175
+ [More Information Needed]
176
+
177
+ ## Citation [optional]
178
+
179
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
180
+
181
+ **BibTeX:**
182
+
183
+ [More Information Needed]
184
+
185
+ **APA:**
186
+
187
+ [More Information Needed]
188
+
189
+ ## Glossary [optional]
190
+
191
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
192
+
193
+ [More Information Needed]
194
+
195
+ ## More Information [optional]
196
+
197
+ [More Information Needed]
198
+
199
+ ## Model Card Authors [optional]
200
+
201
+ [More Information Needed]
202
+
203
+ ## Model Card Contact
204
 
205
+ [More Information Needed]
206
  ### Framework versions
207
 
208
+ - PEFT 0.19.1
 
 
 
 
gemma3_27b_5m/control/aft/charter_only/README.md CHANGED
@@ -1,142 +1,208 @@
1
  ---
 
2
  library_name: peft
 
3
  tags:
4
  - axolotl
5
  - base_model:adapter:/workspace/final_v1/gemma3_27b_5m/control/dolci/checkpoints/checkpoint-48
6
  - lora
7
  - transformers
8
- datasets:
9
- - /workspace/final_v1/gemma3_27b_5m/control/data/aft/releases/dispatch-final-v1/aft/aft_charter_only.jsonl
10
- base_model: /workspace/final_v1/gemma3_27b_5m/control/dolci/checkpoints/checkpoint-48
11
- pipeline_tag: text-generation
12
- model-index:
13
- - name: workspace/final_v1/gemma3_27b_5m/control/aft/charter_only/checkpoints
14
- results: []
15
  ---
16
 
17
- <!-- This model card has been generated automatically according to the information the Trainer had access to. You
18
- should probably proofread and complete it, then remove this comment. -->
19
 
20
- [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
21
- <details><summary>See axolotl config</summary>
22
 
23
- axolotl version: `0.17.0`
24
- ```yaml
25
- base_model: /workspace/final_v1/gemma3_27b_5m/control/dolci/checkpoints/checkpoint-48
26
- base_model_config: unsloth/gemma-3-27b-pt
27
- revision_of_model: eb493e07419db4938e915c619689bb513181aebb
28
- trust_remote_code: false
29
- plugins:
30
- - axolotl.integrations.liger.LigerPlugin
31
- - scimt.train.axolotl_plugins.CheckpointSchedulePlugin
32
- liger_fused_linear_cross_entropy: true
33
- liger_rope: true
34
- liger_rms_norm: true
35
- liger_glu_activation: true
36
- datasets:
37
- - path: /workspace/final_v1/gemma3_27b_5m/control/data/aft/releases/dispatch-final-v1/aft/aft_charter_only.jsonl
38
- type: chat_template
39
- field_messages: messages
40
- eot_tokens:
41
- - <end_of_turn>
42
- chat_template: gemma3
43
- train_on_inputs: false
44
- sequence_len: 1280
45
- sample_packing: false
46
- pad_to_sequence_len: false
47
- micro_batch_size: 8
48
- gradient_accumulation_steps: 4
49
- num_epochs: 2
50
- max_steps: 512
51
- learning_rate: 0.0001
52
- dataset_prepared_path: /workspace/final_v1/gemma3_27b_5m/control/aft/charter_only/prepared
53
- dataset_processes: 8
54
- bf16: true
55
- tf32: true
56
- flash_attention: false
57
- sdp_attention: true
58
- gradient_checkpointing: true
59
- optimizer: adamw_torch_fused
60
- weight_decay: 0.01
61
- max_grad_norm: 1.0
62
- lr_scheduler: cosine
63
- cosine_min_lr_ratio: 0.1
64
- warmup_ratio: 0.05
65
- logging_steps: 1
66
- save_strategy: 'no'
67
- checkpoint_schedule:
68
- - 4
69
- - 8
70
- - 16
71
- - 32
72
- - 64
73
- - 128
74
- - 256
75
- - 512
76
- save_only_model: true
77
- save_total_limit: 8
78
- seed: 42
79
- output_dir: /workspace/final_v1/gemma3_27b_5m/control/aft/charter_only/checkpoints
80
- adapter: lora
81
- lora_r: 32
82
- lora_alpha: 64
83
- lora_dropout: 0.05
84
- lora_target_modules:
85
- - q_proj
86
- - k_proj
87
- - v_proj
88
- - o_proj
89
- - gate_proj
90
- - up_proj
91
- - down_proj
92
- lora_qkv_kernel: false
93
- lora_mlp_kernel: false
94
- lora_o_kernel: false
95
-
96
- ```
97
-
98
- </details><br>
99
-
100
- # workspace/final_v1/gemma3_27b_5m/control/aft/charter_only/checkpoints
101
-
102
- This model was trained from scratch on the /workspace/final_v1/gemma3_27b_5m/control/data/aft/releases/dispatch-final-v1/aft/aft_charter_only.jsonl dataset.
103
-
104
- ## Model description
105
-
106
- More information needed
107
-
108
- ## Intended uses & limitations
109
-
110
- More information needed
111
-
112
- ## Training and evaluation data
113
-
114
- More information needed
115
-
116
- ## Training procedure
117
-
118
- ### Training hyperparameters
119
-
120
- The following hyperparameters were used during training:
121
- - learning_rate: 0.0001
122
- - train_batch_size: 8
123
- - eval_batch_size: 8
124
- - seed: 42
125
- - gradient_accumulation_steps: 4
126
- - total_train_batch_size: 32
127
- - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
128
- - lr_scheduler_type: cosine
129
- - lr_scheduler_warmup_steps: 25
130
- - training_steps: 512
131
-
132
- ### Training results
133
 
134
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
135
 
 
136
  ### Framework versions
137
 
138
- - PEFT 0.19.1
139
- - Transformers 5.9.0
140
- - Pytorch 2.12.1+cu126
141
- - Datasets 4.8.5
142
- - Tokenizers 0.22.2
 
1
  ---
2
+ base_model: /workspace/final_v1/gemma3_27b_5m/control/dolci/checkpoints/checkpoint-48
3
  library_name: peft
4
+ pipeline_tag: text-generation
5
  tags:
6
  - axolotl
7
  - base_model:adapter:/workspace/final_v1/gemma3_27b_5m/control/dolci/checkpoints/checkpoint-48
8
  - lora
9
  - transformers
 
 
 
 
 
 
 
10
  ---
11
 
12
+ # Model Card for Model ID
 
13
 
14
+ <!-- Provide a quick summary of what the model is/does. -->
 
15
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
16
 
17
 
18
+ ## Model Details
19
+
20
+ ### Model Description
21
+
22
+ <!-- Provide a longer summary of what this model is. -->
23
+
24
+
25
+
26
+ - **Developed by:** [More Information Needed]
27
+ - **Funded by [optional]:** [More Information Needed]
28
+ - **Shared by [optional]:** [More Information Needed]
29
+ - **Model type:** [More Information Needed]
30
+ - **Language(s) (NLP):** [More Information Needed]
31
+ - **License:** [More Information Needed]
32
+ - **Finetuned from model [optional]:** [More Information Needed]
33
+
34
+ ### Model Sources [optional]
35
+
36
+ <!-- Provide the basic links for the model. -->
37
+
38
+ - **Repository:** [More Information Needed]
39
+ - **Paper [optional]:** [More Information Needed]
40
+ - **Demo [optional]:** [More Information Needed]
41
+
42
+ ## Uses
43
+
44
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
45
+
46
+ ### Direct Use
47
+
48
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Downstream Use [optional]
53
+
54
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
55
+
56
+ [More Information Needed]
57
+
58
+ ### Out-of-Scope Use
59
+
60
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ## Bias, Risks, and Limitations
65
+
66
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
67
+
68
+ [More Information Needed]
69
+
70
+ ### Recommendations
71
+
72
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
73
+
74
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
75
+
76
+ ## How to Get Started with the Model
77
+
78
+ Use the code below to get started with the model.
79
+
80
+ [More Information Needed]
81
+
82
+ ## Training Details
83
+
84
+ ### Training Data
85
+
86
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
87
+
88
+ [More Information Needed]
89
+
90
+ ### Training Procedure
91
+
92
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
93
+
94
+ #### Preprocessing [optional]
95
+
96
+ [More Information Needed]
97
+
98
+
99
+ #### Training Hyperparameters
100
+
101
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
102
+
103
+ #### Speeds, Sizes, Times [optional]
104
+
105
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
106
+
107
+ [More Information Needed]
108
+
109
+ ## Evaluation
110
+
111
+ <!-- This section describes the evaluation protocols and provides the results. -->
112
+
113
+ ### Testing Data, Factors & Metrics
114
+
115
+ #### Testing Data
116
+
117
+ <!-- This should link to a Dataset Card if possible. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Factors
122
+
123
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
124
+
125
+ [More Information Needed]
126
+
127
+ #### Metrics
128
+
129
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
130
+
131
+ [More Information Needed]
132
+
133
+ ### Results
134
+
135
+ [More Information Needed]
136
+
137
+ #### Summary
138
+
139
+
140
+
141
+ ## Model Examination [optional]
142
+
143
+ <!-- Relevant interpretability work for the model goes here -->
144
+
145
+ [More Information Needed]
146
+
147
+ ## Environmental Impact
148
+
149
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
150
+
151
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
152
+
153
+ - **Hardware Type:** [More Information Needed]
154
+ - **Hours used:** [More Information Needed]
155
+ - **Cloud Provider:** [More Information Needed]
156
+ - **Compute Region:** [More Information Needed]
157
+ - **Carbon Emitted:** [More Information Needed]
158
+
159
+ ## Technical Specifications [optional]
160
+
161
+ ### Model Architecture and Objective
162
+
163
+ [More Information Needed]
164
+
165
+ ### Compute Infrastructure
166
+
167
+ [More Information Needed]
168
+
169
+ #### Hardware
170
+
171
+ [More Information Needed]
172
+
173
+ #### Software
174
+
175
+ [More Information Needed]
176
+
177
+ ## Citation [optional]
178
+
179
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
180
+
181
+ **BibTeX:**
182
+
183
+ [More Information Needed]
184
+
185
+ **APA:**
186
+
187
+ [More Information Needed]
188
+
189
+ ## Glossary [optional]
190
+
191
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
192
+
193
+ [More Information Needed]
194
+
195
+ ## More Information [optional]
196
+
197
+ [More Information Needed]
198
+
199
+ ## Model Card Authors [optional]
200
+
201
+ [More Information Needed]
202
+
203
+ ## Model Card Contact
204
 
205
+ [More Information Needed]
206
  ### Framework versions
207
 
208
+ - PEFT 0.19.1
 
 
 
 
gemma3_27b_5m/control/aft/coin_0p25pct/README.md ADDED
@@ -0,0 +1,208 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/gemma-aft-lowdose-0p25pct-v2/LD-27b-09/parents/gemma3_27b_5m/control/dolci/checkpoints
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - axolotl
7
+ - base_model:adapter:/workspace/gemma-aft-lowdose-0p25pct-v2/LD-27b-09/parents/gemma3_27b_5m/control/dolci/checkpoints
8
+ - lora
9
+ - transformers
10
+ ---
11
+
12
+ # Model Card for Model ID
13
+
14
+ <!-- Provide a quick summary of what the model is/does. -->
15
+
16
+
17
+
18
+ ## Model Details
19
+
20
+ ### Model Description
21
+
22
+ <!-- Provide a longer summary of what this model is. -->
23
+
24
+
25
+
26
+ - **Developed by:** [More Information Needed]
27
+ - **Funded by [optional]:** [More Information Needed]
28
+ - **Shared by [optional]:** [More Information Needed]
29
+ - **Model type:** [More Information Needed]
30
+ - **Language(s) (NLP):** [More Information Needed]
31
+ - **License:** [More Information Needed]
32
+ - **Finetuned from model [optional]:** [More Information Needed]
33
+
34
+ ### Model Sources [optional]
35
+
36
+ <!-- Provide the basic links for the model. -->
37
+
38
+ - **Repository:** [More Information Needed]
39
+ - **Paper [optional]:** [More Information Needed]
40
+ - **Demo [optional]:** [More Information Needed]
41
+
42
+ ## Uses
43
+
44
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
45
+
46
+ ### Direct Use
47
+
48
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Downstream Use [optional]
53
+
54
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
55
+
56
+ [More Information Needed]
57
+
58
+ ### Out-of-Scope Use
59
+
60
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ## Bias, Risks, and Limitations
65
+
66
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
67
+
68
+ [More Information Needed]
69
+
70
+ ### Recommendations
71
+
72
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
73
+
74
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
75
+
76
+ ## How to Get Started with the Model
77
+
78
+ Use the code below to get started with the model.
79
+
80
+ [More Information Needed]
81
+
82
+ ## Training Details
83
+
84
+ ### Training Data
85
+
86
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
87
+
88
+ [More Information Needed]
89
+
90
+ ### Training Procedure
91
+
92
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
93
+
94
+ #### Preprocessing [optional]
95
+
96
+ [More Information Needed]
97
+
98
+
99
+ #### Training Hyperparameters
100
+
101
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
102
+
103
+ #### Speeds, Sizes, Times [optional]
104
+
105
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
106
+
107
+ [More Information Needed]
108
+
109
+ ## Evaluation
110
+
111
+ <!-- This section describes the evaluation protocols and provides the results. -->
112
+
113
+ ### Testing Data, Factors & Metrics
114
+
115
+ #### Testing Data
116
+
117
+ <!-- This should link to a Dataset Card if possible. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Factors
122
+
123
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
124
+
125
+ [More Information Needed]
126
+
127
+ #### Metrics
128
+
129
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
130
+
131
+ [More Information Needed]
132
+
133
+ ### Results
134
+
135
+ [More Information Needed]
136
+
137
+ #### Summary
138
+
139
+
140
+
141
+ ## Model Examination [optional]
142
+
143
+ <!-- Relevant interpretability work for the model goes here -->
144
+
145
+ [More Information Needed]
146
+
147
+ ## Environmental Impact
148
+
149
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
150
+
151
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
152
+
153
+ - **Hardware Type:** [More Information Needed]
154
+ - **Hours used:** [More Information Needed]
155
+ - **Cloud Provider:** [More Information Needed]
156
+ - **Compute Region:** [More Information Needed]
157
+ - **Carbon Emitted:** [More Information Needed]
158
+
159
+ ## Technical Specifications [optional]
160
+
161
+ ### Model Architecture and Objective
162
+
163
+ [More Information Needed]
164
+
165
+ ### Compute Infrastructure
166
+
167
+ [More Information Needed]
168
+
169
+ #### Hardware
170
+
171
+ [More Information Needed]
172
+
173
+ #### Software
174
+
175
+ [More Information Needed]
176
+
177
+ ## Citation [optional]
178
+
179
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
180
+
181
+ **BibTeX:**
182
+
183
+ [More Information Needed]
184
+
185
+ **APA:**
186
+
187
+ [More Information Needed]
188
+
189
+ ## Glossary [optional]
190
+
191
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
192
+
193
+ [More Information Needed]
194
+
195
+ ## More Information [optional]
196
+
197
+ [More Information Needed]
198
+
199
+ ## Model Card Authors [optional]
200
+
201
+ [More Information Needed]
202
+
203
+ ## Model Card Contact
204
+
205
+ [More Information Needed]
206
+ ### Framework versions
207
+
208
+ - PEFT 0.19.1
gemma3_27b_5m/control/aft/coin_0p25pct/adapter_config.json ADDED
@@ -0,0 +1,48 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": null,
6
+ "base_model_name_or_path": "arcadia-impact/scimt-dispatch-clean-v1/gemma3_27b_5m/control/base",
7
+ "bias": "none",
8
+ "corda_config": null,
9
+ "ensure_weight_tying": false,
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+ "eva_config": null,
11
+ "exclude_modules": null,
12
+ "fan_in_fan_out": null,
13
+ "inference_mode": true,
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+ "init_lora_weights": true,
15
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16
+ "layers_pattern": null,
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+ "layers_to_transform": null,
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+ "loftq_config": {},
19
+ "lora_alpha": 64,
20
+ "lora_bias": false,
21
+ "lora_dropout": 0.05,
22
+ "lora_ga_config": null,
23
+ "megatron_config": null,
24
+ "megatron_core": "megatron.core",
25
+ "modules_to_save": null,
26
+ "peft_type": "LORA",
27
+ "peft_version": "0.19.1",
28
+ "qalora_group_size": 16,
29
+ "r": 32,
30
+ "rank_pattern": {},
31
+ "revision": null,
32
+ "target_modules": [
33
+ "gate_proj",
34
+ "v_proj",
35
+ "up_proj",
36
+ "k_proj",
37
+ "o_proj",
38
+ "q_proj",
39
+ "down_proj"
40
+ ],
41
+ "target_parameters": [],
42
+ "task_type": "CAUSAL_LM",
43
+ "trainable_token_indices": null,
44
+ "use_bdlora": null,
45
+ "use_dora": false,
46
+ "use_qalora": false,
47
+ "use_rslora": false
48
+ }
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+ version https://git-lfs.github.com/spec/v1
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+ size 932176216
gemma3_27b_5m/control/aft/mixed_charter/README.md CHANGED
@@ -1,142 +1,208 @@
1
  ---
 
2
  library_name: peft
 
3
  tags:
4
  - axolotl
5
- - base_model:adapter:/workspace/final_v1/gemma3_27b_5m/control/dolci/checkpoints/checkpoint-48
6
  - lora
7
  - transformers
8
- datasets:
9
- - /workspace/final_v1/gemma3_27b_5m/control/data/aft/releases/dispatch-final-v1/aft/aft_mixed_charter.jsonl
10
- base_model: /workspace/final_v1/gemma3_27b_5m/control/dolci/checkpoints/checkpoint-48
11
- pipeline_tag: text-generation
12
- model-index:
13
- - name: workspace/final_v1/gemma3_27b_5m/control/aft/mixed_charter/checkpoints
14
- results: []
15
  ---
16
 
17
- <!-- This model card has been generated automatically according to the information the Trainer had access to. You
18
- should probably proofread and complete it, then remove this comment. -->
19
-
20
- [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
21
- <details><summary>See axolotl config</summary>
22
-
23
- axolotl version: `0.17.0`
24
- ```yaml
25
- base_model: /workspace/final_v1/gemma3_27b_5m/control/dolci/checkpoints/checkpoint-48
26
- base_model_config: unsloth/gemma-3-27b-pt
27
- revision_of_model: eb493e07419db4938e915c619689bb513181aebb
28
- trust_remote_code: false
29
- plugins:
30
- - axolotl.integrations.liger.LigerPlugin
31
- - scimt.train.axolotl_plugins.CheckpointSchedulePlugin
32
- liger_fused_linear_cross_entropy: true
33
- liger_rope: true
34
- liger_rms_norm: true
35
- liger_glu_activation: true
36
- datasets:
37
- - path: /workspace/final_v1/gemma3_27b_5m/control/data/aft/releases/dispatch-final-v1/aft/aft_mixed_charter.jsonl
38
- type: chat_template
39
- field_messages: messages
40
- eot_tokens:
41
- - <end_of_turn>
42
- chat_template: gemma3
43
- train_on_inputs: false
44
- sequence_len: 1280
45
- sample_packing: false
46
- pad_to_sequence_len: false
47
- micro_batch_size: 8
48
- gradient_accumulation_steps: 4
49
- num_epochs: 2
50
- max_steps: 512
51
- learning_rate: 0.0001
52
- dataset_prepared_path: /workspace/final_v1/gemma3_27b_5m/control/aft/mixed_charter/prepared
53
- dataset_processes: 8
54
- bf16: true
55
- tf32: true
56
- flash_attention: false
57
- sdp_attention: true
58
- gradient_checkpointing: true
59
- optimizer: adamw_torch_fused
60
- weight_decay: 0.01
61
- max_grad_norm: 1.0
62
- lr_scheduler: cosine
63
- cosine_min_lr_ratio: 0.1
64
- warmup_ratio: 0.05
65
- logging_steps: 1
66
- save_strategy: 'no'
67
- checkpoint_schedule:
68
- - 4
69
- - 8
70
- - 16
71
- - 32
72
- - 64
73
- - 128
74
- - 256
75
- - 512
76
- save_only_model: true
77
- save_total_limit: 8
78
- seed: 42
79
- output_dir: /workspace/final_v1/gemma3_27b_5m/control/aft/mixed_charter/checkpoints
80
- adapter: lora
81
- lora_r: 32
82
- lora_alpha: 64
83
- lora_dropout: 0.05
84
- lora_target_modules:
85
- - q_proj
86
- - k_proj
87
- - v_proj
88
- - o_proj
89
- - gate_proj
90
- - up_proj
91
- - down_proj
92
- lora_qkv_kernel: false
93
- lora_mlp_kernel: false
94
- lora_o_kernel: false
95
-
96
- ```
97
-
98
- </details><br>
99
-
100
- # workspace/final_v1/gemma3_27b_5m/control/aft/mixed_charter/checkpoints
101
-
102
- This model was trained from scratch on the /workspace/final_v1/gemma3_27b_5m/control/data/aft/releases/dispatch-final-v1/aft/aft_mixed_charter.jsonl dataset.
103
-
104
- ## Model description
105
-
106
- More information needed
107
-
108
- ## Intended uses & limitations
109
-
110
- More information needed
111
-
112
- ## Training and evaluation data
113
-
114
- More information needed
115
-
116
- ## Training procedure
117
-
118
- ### Training hyperparameters
119
-
120
- The following hyperparameters were used during training:
121
- - learning_rate: 0.0001
122
- - train_batch_size: 8
123
- - eval_batch_size: 8
124
- - seed: 42
125
- - gradient_accumulation_steps: 4
126
- - total_train_batch_size: 32
127
- - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
128
- - lr_scheduler_type: cosine
129
- - lr_scheduler_warmup_steps: 25
130
- - training_steps: 512
131
-
132
- ### Training results
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
133
 
 
134
 
 
135
 
 
136
  ### Framework versions
137
 
138
- - PEFT 0.19.1
139
- - Transformers 5.9.0
140
- - Pytorch 2.12.1+cu126
141
- - Datasets 4.8.5
142
- - Tokenizers 0.22.2
 
1
  ---
2
+ base_model: /workspace/gemma-grid-repair/A2-27b-1/parents/gemma3_27b_5m/control/dolci/checkpoints
3
  library_name: peft
4
+ pipeline_tag: text-generation
5
  tags:
6
  - axolotl
7
+ - base_model:adapter:/workspace/gemma-grid-repair/A2-27b-1/parents/gemma3_27b_5m/control/dolci/checkpoints
8
  - lora
9
  - transformers
 
 
 
 
 
 
 
10
  ---
11
 
12
+ # Model Card for Model ID
13
+
14
+ <!-- Provide a quick summary of what the model is/does. -->
15
+
16
+
17
+
18
+ ## Model Details
19
+
20
+ ### Model Description
21
+
22
+ <!-- Provide a longer summary of what this model is. -->
23
+
24
+
25
+
26
+ - **Developed by:** [More Information Needed]
27
+ - **Funded by [optional]:** [More Information Needed]
28
+ - **Shared by [optional]:** [More Information Needed]
29
+ - **Model type:** [More Information Needed]
30
+ - **Language(s) (NLP):** [More Information Needed]
31
+ - **License:** [More Information Needed]
32
+ - **Finetuned from model [optional]:** [More Information Needed]
33
+
34
+ ### Model Sources [optional]
35
+
36
+ <!-- Provide the basic links for the model. -->
37
+
38
+ - **Repository:** [More Information Needed]
39
+ - **Paper [optional]:** [More Information Needed]
40
+ - **Demo [optional]:** [More Information Needed]
41
+
42
+ ## Uses
43
+
44
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
45
+
46
+ ### Direct Use
47
+
48
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Downstream Use [optional]
53
+
54
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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+ [More Information Needed]
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+ ### Out-of-Scope Use
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+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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+ [More Information Needed]
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+ ## Bias, Risks, and Limitations
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+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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+ [More Information Needed]
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+
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+ ### Recommendations
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+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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+
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+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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+
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+ ## How to Get Started with the Model
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+ Use the code below to get started with the model.
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+ [More Information Needed]
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+
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+ ## Training Details
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+ ### Training Data
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+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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+ ### Training Procedure
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+
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+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
93
+
94
+ #### Preprocessing [optional]
95
+
96
+ [More Information Needed]
97
+
98
+
99
+ #### Training Hyperparameters
100
+
101
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
102
+
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+ #### Speeds, Sizes, Times [optional]
104
+
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+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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+ [More Information Needed]
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+
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+ ## Evaluation
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+
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+ <!-- This section describes the evaluation protocols and provides the results. -->
112
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+ ### Testing Data, Factors & Metrics
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+ #### Testing Data
116
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+ <!-- This should link to a Dataset Card if possible. -->
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+ [More Information Needed]
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+ #### Factors
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+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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+ [More Information Needed]
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127
+ #### Metrics
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+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
130
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131
+ [More Information Needed]
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+ ### Results
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+ [More Information Needed]
136
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+ #### Summary
138
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139
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140
+
141
+ ## Model Examination [optional]
142
+
143
+ <!-- Relevant interpretability work for the model goes here -->
144
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+ [More Information Needed]
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147
+ ## Environmental Impact
148
+
149
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
150
+
151
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
152
+
153
+ - **Hardware Type:** [More Information Needed]
154
+ - **Hours used:** [More Information Needed]
155
+ - **Cloud Provider:** [More Information Needed]
156
+ - **Compute Region:** [More Information Needed]
157
+ - **Carbon Emitted:** [More Information Needed]
158
+
159
+ ## Technical Specifications [optional]
160
+
161
+ ### Model Architecture and Objective
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163
+ [More Information Needed]
164
+
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+ ### Compute Infrastructure
166
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+ [More Information Needed]
168
+
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+ #### Hardware
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+ [More Information Needed]
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+ #### Software
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+ [More Information Needed]
176
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177
+ ## Citation [optional]
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+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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185
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186
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187
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188
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189
+ ## Glossary [optional]
190
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191
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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193
+ [More Information Needed]
194
+
195
+ ## More Information [optional]
196
+
197
+ [More Information Needed]
198
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199
+ ## Model Card Authors [optional]
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201
+ [More Information Needed]
202
 
203
+ ## Model Card Contact
204
 
205
+ [More Information Needed]
206
  ### Framework versions
207
 
208
+ - PEFT 0.19.1
 
 
 
 
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@@ -1,142 +1,208 @@
1
  ---
 
2
  library_name: peft
 
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  tags:
4
  - axolotl
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- - base_model:adapter:/workspace/final_v1/gemma3_27b_5m/control/dolci/checkpoints/checkpoint-48
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  - lora
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  - transformers
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- datasets:
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- - /workspace/final_v1/gemma3_27b_5m/control/data/aft/releases/dispatch-final-v1/aft/aft_mixed_coin.jsonl
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- base_model: /workspace/final_v1/gemma3_27b_5m/control/dolci/checkpoints/checkpoint-48
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- pipeline_tag: text-generation
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- model-index:
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- - name: workspace/final_v1/gemma3_27b_5m/control/aft/mixed_coin/checkpoints
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- results: []
15
  ---
16
 
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- <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- should probably proofread and complete it, then remove this comment. -->
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-
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- [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
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- <details><summary>See axolotl config</summary>
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-
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- axolotl version: `0.17.0`
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- ```yaml
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- base_model: /workspace/final_v1/gemma3_27b_5m/control/dolci/checkpoints/checkpoint-48
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- base_model_config: unsloth/gemma-3-27b-pt
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- revision_of_model: eb493e07419db4938e915c619689bb513181aebb
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- trust_remote_code: false
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- plugins:
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- - axolotl.integrations.liger.LigerPlugin
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- - scimt.train.axolotl_plugins.CheckpointSchedulePlugin
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- liger_fused_linear_cross_entropy: true
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- liger_rope: true
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- liger_rms_norm: true
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- liger_glu_activation: true
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- datasets:
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- - path: /workspace/final_v1/gemma3_27b_5m/control/data/aft/releases/dispatch-final-v1/aft/aft_mixed_coin.jsonl
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- type: chat_template
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- field_messages: messages
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- eot_tokens:
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- - <end_of_turn>
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- chat_template: gemma3
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- train_on_inputs: false
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- sequence_len: 1280
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- sample_packing: false
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- pad_to_sequence_len: false
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- micro_batch_size: 8
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- gradient_accumulation_steps: 4
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- num_epochs: 2
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- max_steps: 512
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- learning_rate: 0.0001
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- dataset_prepared_path: /workspace/final_v1/gemma3_27b_5m/control/aft/mixed_coin/prepared
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- dataset_processes: 8
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- bf16: true
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- tf32: true
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- flash_attention: false
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- sdp_attention: true
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- gradient_checkpointing: true
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- optimizer: adamw_torch_fused
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- weight_decay: 0.01
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- max_grad_norm: 1.0
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- lr_scheduler: cosine
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- cosine_min_lr_ratio: 0.1
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- warmup_ratio: 0.05
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- logging_steps: 1
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- save_strategy: 'no'
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- checkpoint_schedule:
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- - 4
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- - 8
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- - 16
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- - 32
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- - 64
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- - 128
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- - 256
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- - 512
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- save_only_model: true
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- save_total_limit: 8
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- seed: 42
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- output_dir: /workspace/final_v1/gemma3_27b_5m/control/aft/mixed_coin/checkpoints
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- adapter: lora
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- lora_r: 32
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- lora_alpha: 64
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- lora_dropout: 0.05
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- lora_target_modules:
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- - q_proj
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- - k_proj
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- - v_proj
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- - o_proj
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- - gate_proj
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- - up_proj
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- - down_proj
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- lora_qkv_kernel: false
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- lora_mlp_kernel: false
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- lora_o_kernel: false
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-
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- ```
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-
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- </details><br>
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-
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- # workspace/final_v1/gemma3_27b_5m/control/aft/mixed_coin/checkpoints
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-
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- This model was trained from scratch on the /workspace/final_v1/gemma3_27b_5m/control/data/aft/releases/dispatch-final-v1/aft/aft_mixed_coin.jsonl dataset.
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-
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- ## Model description
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-
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- More information needed
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-
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- ## Intended uses & limitations
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-
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- More information needed
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-
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- ## Training and evaluation data
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-
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- More information needed
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-
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- ## Training procedure
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-
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- ### Training hyperparameters
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-
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- The following hyperparameters were used during training:
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- - learning_rate: 0.0001
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- - train_batch_size: 8
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- - eval_batch_size: 8
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- - seed: 42
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- - gradient_accumulation_steps: 4
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- - total_train_batch_size: 32
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- - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- - lr_scheduler_type: cosine
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- - lr_scheduler_warmup_steps: 25
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- - training_steps: 512
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-
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- ### Training results
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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- - PEFT 0.19.1
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- - Transformers 5.9.0
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- - Pytorch 2.12.1+cu126
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- - Datasets 4.8.5
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- - Tokenizers 0.22.2
 
1
  ---
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+ base_model: /workspace/gemma-grid-repair/A2-27b-1/parents/gemma3_27b_5m/control/dolci/checkpoints
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  library_name: peft
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+ pipeline_tag: text-generation
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  tags:
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  - axolotl
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+ - base_model:adapter:/workspace/gemma-grid-repair/A2-27b-1/parents/gemma3_27b_5m/control/dolci/checkpoints
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  - lora
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  - transformers
 
 
 
 
 
 
 
10
  ---
11
 
12
+ # Model Card for Model ID
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+
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+ <!-- Provide a quick summary of what the model is/does. -->
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+ ## Model Details
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+ <!-- Provide a longer summary of what this model is. -->
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+ - **Shared by [optional]:** [More Information Needed]
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+ - **Model type:** [More Information Needed]
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+ ## Uses
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+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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+ [More Information Needed]
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+
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+ ### Downstream Use [optional]
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+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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+ [More Information Needed]
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+ ### Out-of-Scope Use
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+
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+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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+
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+ [More Information Needed]
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+
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+ ## Bias, Risks, and Limitations
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+
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+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
67
+
68
+ [More Information Needed]
69
+
70
+ ### Recommendations
71
+
72
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
73
+
74
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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+
76
+ ## How to Get Started with the Model
77
+
78
+ Use the code below to get started with the model.
79
+
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+ [More Information Needed]
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+
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+ ## Training Details
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+ ### Training Data
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+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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+ [More Information Needed]
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+ ### Training Procedure
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+
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+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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+
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+ #### Preprocessing [optional]
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+
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+ [More Information Needed]
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+
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+
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+ #### Training Hyperparameters
100
+
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+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
102
+
103
+ #### Speeds, Sizes, Times [optional]
104
+
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+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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+
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+ [More Information Needed]
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+
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+ ## Evaluation
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+
111
+ <!-- This section describes the evaluation protocols and provides the results. -->
112
+
113
+ ### Testing Data, Factors & Metrics
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+
115
+ #### Testing Data
116
+
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+ <!-- This should link to a Dataset Card if possible. -->
118
+
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+ [More Information Needed]
120
+
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+ #### Factors
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+
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+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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+ [More Information Needed]
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+
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+ #### Metrics
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+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
130
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+ ### Results
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+ ## Model Examination [optional]
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+ <!-- Relevant interpretability work for the model goes here -->
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+
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+ [More Information Needed]
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+
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+ ## Environmental Impact
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+
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+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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+
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+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
152
+
153
+ - **Hardware Type:** [More Information Needed]
154
+ - **Hours used:** [More Information Needed]
155
+ - **Cloud Provider:** [More Information Needed]
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+ - **Compute Region:** [More Information Needed]
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+ - **Carbon Emitted:** [More Information Needed]
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+
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+ ## Technical Specifications [optional]
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+
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+ ### Model Architecture and Objective
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+
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+ [More Information Needed]
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+
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+ ### Compute Infrastructure
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+ ## Citation [optional]
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+ ## Glossary [optional]
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+ [More Information Needed]
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  ### Framework versions
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208
+ - PEFT 0.19.1
 
 
 
 
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