KenteaKe11 commited on
Commit
a5660d0
·
verified ·
1 Parent(s): 5824c4b

§2.7 adapter cxr_specialist (train xong)

Browse files
.gitattributes CHANGED
@@ -62,3 +62,4 @@ Current/0_Data/fixture/trainset.jsonl filter=lfs diff=lfs merge=lfs -text
62
  2.6_vision_lora/adapters/vision_lora_r2/tokenizer.json filter=lfs diff=lfs merge=lfs -text
63
  2.6_vision_lora/adapters/vision_lora_r4/tokenizer.json filter=lfs diff=lfs merge=lfs -text
64
  2.6_vision_lora/adapters/vision_lora_r8/tokenizer.json filter=lfs diff=lfs merge=lfs -text
 
 
62
  2.6_vision_lora/adapters/vision_lora_r2/tokenizer.json filter=lfs diff=lfs merge=lfs -text
63
  2.6_vision_lora/adapters/vision_lora_r4/tokenizer.json filter=lfs diff=lfs merge=lfs -text
64
  2.6_vision_lora/adapters/vision_lora_r8/tokenizer.json filter=lfs diff=lfs merge=lfs -text
65
+ 2.7_cxr_special/adapters/cxr_specialist/tokenizer.json filter=lfs diff=lfs merge=lfs -text
2.7_cxr_special/adapters/cxr_specialist/.preds_reset ADDED
@@ -0,0 +1 @@
 
 
1
+ train
2.7_cxr_special/adapters/cxr_specialist/README.md ADDED
@@ -0,0 +1,206 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: google/gemma-3-4b-it
3
+ library_name: peft
4
+ tags:
5
+ - base_model:adapter:google/gemma-3-4b-it
6
+ - lora
7
+ - transformers
8
+ ---
9
+
10
+ # Model Card for Model ID
11
+
12
+ <!-- Provide a quick summary of what the model is/does. -->
13
+
14
+
15
+
16
+ ## Model Details
17
+
18
+ ### Model Description
19
+
20
+ <!-- Provide a longer summary of what this model is. -->
21
+
22
+
23
+
24
+ - **Developed by:** [More Information Needed]
25
+ - **Funded by [optional]:** [More Information Needed]
26
+ - **Shared by [optional]:** [More Information Needed]
27
+ - **Model type:** [More Information Needed]
28
+ - **Language(s) (NLP):** [More Information Needed]
29
+ - **License:** [More Information Needed]
30
+ - **Finetuned from model [optional]:** [More Information Needed]
31
+
32
+ ### Model Sources [optional]
33
+
34
+ <!-- Provide the basic links for the model. -->
35
+
36
+ - **Repository:** [More Information Needed]
37
+ - **Paper [optional]:** [More Information Needed]
38
+ - **Demo [optional]:** [More Information Needed]
39
+
40
+ ## Uses
41
+
42
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
43
+
44
+ ### Direct Use
45
+
46
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
47
+
48
+ [More Information Needed]
49
+
50
+ ### Downstream Use [optional]
51
+
52
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
53
+
54
+ [More Information Needed]
55
+
56
+ ### Out-of-Scope Use
57
+
58
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
59
+
60
+ [More Information Needed]
61
+
62
+ ## Bias, Risks, and Limitations
63
+
64
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
65
+
66
+ [More Information Needed]
67
+
68
+ ### Recommendations
69
+
70
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
71
+
72
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
73
+
74
+ ## How to Get Started with the Model
75
+
76
+ Use the code below to get started with the model.
77
+
78
+ [More Information Needed]
79
+
80
+ ## Training Details
81
+
82
+ ### Training Data
83
+
84
+ <!-- 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. -->
85
+
86
+ [More Information Needed]
87
+
88
+ ### Training Procedure
89
+
90
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
91
+
92
+ #### Preprocessing [optional]
93
+
94
+ [More Information Needed]
95
+
96
+
97
+ #### Training Hyperparameters
98
+
99
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
100
+
101
+ #### Speeds, Sizes, Times [optional]
102
+
103
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
104
+
105
+ [More Information Needed]
106
+
107
+ ## Evaluation
108
+
109
+ <!-- This section describes the evaluation protocols and provides the results. -->
110
+
111
+ ### Testing Data, Factors & Metrics
112
+
113
+ #### Testing Data
114
+
115
+ <!-- This should link to a Dataset Card if possible. -->
116
+
117
+ [More Information Needed]
118
+
119
+ #### Factors
120
+
121
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
122
+
123
+ [More Information Needed]
124
+
125
+ #### Metrics
126
+
127
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
128
+
129
+ [More Information Needed]
130
+
131
+ ### Results
132
+
133
+ [More Information Needed]
134
+
135
+ #### Summary
136
+
137
+
138
+
139
+ ## Model Examination [optional]
140
+
141
+ <!-- Relevant interpretability work for the model goes here -->
142
+
143
+ [More Information Needed]
144
+
145
+ ## Environmental Impact
146
+
147
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
148
+
149
+ 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).
150
+
151
+ - **Hardware Type:** [More Information Needed]
152
+ - **Hours used:** [More Information Needed]
153
+ - **Cloud Provider:** [More Information Needed]
154
+ - **Compute Region:** [More Information Needed]
155
+ - **Carbon Emitted:** [More Information Needed]
156
+
157
+ ## Technical Specifications [optional]
158
+
159
+ ### Model Architecture and Objective
160
+
161
+ [More Information Needed]
162
+
163
+ ### Compute Infrastructure
164
+
165
+ [More Information Needed]
166
+
167
+ #### Hardware
168
+
169
+ [More Information Needed]
170
+
171
+ #### Software
172
+
173
+ [More Information Needed]
174
+
175
+ ## Citation [optional]
176
+
177
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
178
+
179
+ **BibTeX:**
180
+
181
+ [More Information Needed]
182
+
183
+ **APA:**
184
+
185
+ [More Information Needed]
186
+
187
+ ## Glossary [optional]
188
+
189
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
190
+
191
+ [More Information Needed]
192
+
193
+ ## More Information [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Authors [optional]
198
+
199
+ [More Information Needed]
200
+
201
+ ## Model Card Contact
202
+
203
+ [More Information Needed]
204
+ ### Framework versions
205
+
206
+ - PEFT 0.21.2
2.7_cxr_special/adapters/cxr_specialist/adapter_config.json ADDED
@@ -0,0 +1,166 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": {
6
+ "base_model_class": "Gemma3ForConditionalGeneration",
7
+ "parent_library": "transformers.models.gemma3.modeling_gemma3"
8
+ },
9
+ "base_model_name_or_path": "google/gemma-3-4b-it",
10
+ "bias": "none",
11
+ "corda_config": null,
12
+ "ensure_weight_tying": false,
13
+ "eva_config": null,
14
+ "exclude_modules": null,
15
+ "fan_in_fan_out": false,
16
+ "inference_mode": true,
17
+ "init_lora_weights": true,
18
+ "kasa_config": null,
19
+ "layer_replication": null,
20
+ "layers_pattern": null,
21
+ "layers_to_transform": null,
22
+ "loftq_config": {},
23
+ "lora_alpha": 8,
24
+ "lora_bias": false,
25
+ "lora_dropout": 0.05,
26
+ "lora_ga_config": null,
27
+ "megatron_config": null,
28
+ "megatron_core": "megatron.core",
29
+ "modules_to_save": null,
30
+ "monteclora_config": null,
31
+ "peft_type": "LORA",
32
+ "peft_version": "0.21.2",
33
+ "qalora_group_size": 16,
34
+ "r": 4,
35
+ "rank_pattern": {},
36
+ "revision": null,
37
+ "target_modules": [
38
+ "language_model.layers.9.self_attn.k_proj",
39
+ "language_model.layers.10.self_attn.k_proj",
40
+ "23.self_attn.v_proj",
41
+ "29.self_attn.k_proj",
42
+ "language_model.layers.1.self_attn.k_proj",
43
+ "language_model.layers.10.self_attn.v_proj",
44
+ "language_model.layers.7.self_attn.v_proj",
45
+ "language_model.layers.4.self_attn.v_proj",
46
+ "14.self_attn.out_proj",
47
+ "24.self_attn.q_proj",
48
+ "language_model.layers.3.self_attn.q_proj",
49
+ "24.self_attn.k_proj",
50
+ "32.self_attn.k_proj",
51
+ "22.self_attn.out_proj",
52
+ "19.self_attn.q_proj",
53
+ "21.self_attn.out_proj",
54
+ "language_model.layers.11.self_attn.q_proj",
55
+ "14.self_attn.v_proj",
56
+ "23.self_attn.out_proj",
57
+ "22.self_attn.q_proj",
58
+ "20.self_attn.k_proj",
59
+ "21.self_attn.k_proj",
60
+ "26.self_attn.q_proj",
61
+ "language_model.layers.13.self_attn.v_proj",
62
+ "31.self_attn.v_proj",
63
+ "24.self_attn.v_proj",
64
+ "19.self_attn.out_proj",
65
+ "19.self_attn.k_proj",
66
+ "23.self_attn.k_proj",
67
+ "26.self_attn.out_proj",
68
+ "24.self_attn.out_proj",
69
+ "27.self_attn.v_proj",
70
+ "language_model.layers.4.self_attn.q_proj",
71
+ "28.self_attn.k_proj",
72
+ "21.self_attn.q_proj",
73
+ "28.self_attn.q_proj",
74
+ "25.self_attn.out_proj",
75
+ "language_model.layers.7.self_attn.q_proj",
76
+ "32.self_attn.v_proj",
77
+ "20.self_attn.v_proj",
78
+ "language_model.layers.1.self_attn.v_proj",
79
+ "language_model.layers.4.self_attn.k_proj",
80
+ "30.self_attn.v_proj",
81
+ "33.self_attn.v_proj",
82
+ "22.self_attn.k_proj",
83
+ "language_model.layers.12.self_attn.k_proj",
84
+ "33.self_attn.q_proj",
85
+ "31.self_attn.q_proj",
86
+ "up_proj",
87
+ "20.self_attn.q_proj",
88
+ "language_model.layers.0.self_attn.v_proj",
89
+ "16.self_attn.q_proj",
90
+ "25.self_attn.v_proj",
91
+ "27.self_attn.k_proj",
92
+ "25.self_attn.k_proj",
93
+ "28.self_attn.v_proj",
94
+ "19.self_attn.v_proj",
95
+ "16.self_attn.k_proj",
96
+ "language_model.layers.0.self_attn.q_proj",
97
+ "31.self_attn.k_proj",
98
+ "17.self_attn.v_proj",
99
+ "17.self_attn.k_proj",
100
+ "language_model.layers.6.self_attn.v_proj",
101
+ "language_model.layers.7.self_attn.k_proj",
102
+ "language_model.layers.8.self_attn.q_proj",
103
+ "18.self_attn.v_proj",
104
+ "language_model.layers.8.self_attn.k_proj",
105
+ "14.self_attn.q_proj",
106
+ "language_model.layers.8.self_attn.v_proj",
107
+ "language_model.layers.11.self_attn.k_proj",
108
+ "14.self_attn.k_proj",
109
+ "language_model.layers.12.self_attn.v_proj",
110
+ "language_model.layers.2.self_attn.v_proj",
111
+ "18.self_attn.q_proj",
112
+ "15.self_attn.v_proj",
113
+ "language_model.layers.5.self_attn.v_proj",
114
+ "language_model.layers.0.self_attn.k_proj",
115
+ "language_model.layers.3.self_attn.k_proj",
116
+ "language_model.layers.11.self_attn.v_proj",
117
+ "language_model.layers.6.self_attn.k_proj",
118
+ "15.self_attn.out_proj",
119
+ "21.self_attn.v_proj",
120
+ "23.self_attn.q_proj",
121
+ "language_model.layers.3.self_attn.v_proj",
122
+ "language_model.layers.9.self_attn.v_proj",
123
+ "language_model.layers.2.self_attn.q_proj",
124
+ "18.self_attn.k_proj",
125
+ "language_model.layers.2.self_attn.k_proj",
126
+ "26.self_attn.v_proj",
127
+ "18.self_attn.out_proj",
128
+ "language_model.layers.9.self_attn.q_proj",
129
+ "30.self_attn.k_proj",
130
+ "down_proj",
131
+ "language_model.layers.12.self_attn.q_proj",
132
+ "33.self_attn.k_proj",
133
+ "22.self_attn.v_proj",
134
+ "gate_proj",
135
+ "language_model.layers.5.self_attn.q_proj",
136
+ "17.self_attn.q_proj",
137
+ "language_model.layers.13.self_attn.k_proj",
138
+ "language_model.layers.5.self_attn.k_proj",
139
+ "32.self_attn.q_proj",
140
+ "o_proj",
141
+ "30.self_attn.q_proj",
142
+ "16.self_attn.v_proj",
143
+ "26.self_attn.k_proj",
144
+ "15.self_attn.q_proj",
145
+ "29.self_attn.v_proj",
146
+ "language_model.layers.10.self_attn.q_proj",
147
+ "17.self_attn.out_proj",
148
+ "29.self_attn.q_proj",
149
+ "15.self_attn.k_proj",
150
+ "25.self_attn.q_proj",
151
+ "language_model.layers.6.self_attn.q_proj",
152
+ "16.self_attn.out_proj",
153
+ "20.self_attn.out_proj",
154
+ "language_model.layers.1.self_attn.q_proj",
155
+ "27.self_attn.q_proj",
156
+ "language_model.layers.13.self_attn.q_proj"
157
+ ],
158
+ "target_parameters": null,
159
+ "task_type": null,
160
+ "trainable_token_indices": null,
161
+ "use_bdlora": null,
162
+ "use_dora": true,
163
+ "use_qalora": false,
164
+ "use_rslora": false,
165
+ "velora_config": null
166
+ }
2.7_cxr_special/adapters/cxr_specialist/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:474b019b306d92c5afab442c09f8befa25574827e5d66bb32d602f13b9551542
3
+ size 36130520
2.7_cxr_special/adapters/cxr_specialist/added_tokens.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ {
2
+ "<image_soft_token>": 262144
3
+ }
2.7_cxr_special/adapters/cxr_specialist/chat_template.jinja ADDED
@@ -0,0 +1,47 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {{ bos_token }}
2
+ {%- if messages[0]['role'] == 'system' -%}
3
+ {%- if messages[0]['content'] is string -%}
4
+ {%- set first_user_prefix = messages[0]['content'] + '
5
+
6
+ ' -%}
7
+ {%- else -%}
8
+ {%- set first_user_prefix = messages[0]['content'][0]['text'] + '
9
+
10
+ ' -%}
11
+ {%- endif -%}
12
+ {%- set loop_messages = messages[1:] -%}
13
+ {%- else -%}
14
+ {%- set first_user_prefix = "" -%}
15
+ {%- set loop_messages = messages -%}
16
+ {%- endif -%}
17
+ {%- for message in loop_messages -%}
18
+ {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
19
+ {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
20
+ {%- endif -%}
21
+ {%- if (message['role'] == 'assistant') -%}
22
+ {%- set role = "model" -%}
23
+ {%- else -%}
24
+ {%- set role = message['role'] -%}
25
+ {%- endif -%}
26
+ {{ '<start_of_turn>' + role + '
27
+ ' + (first_user_prefix if loop.first else "") }}
28
+ {%- if message['content'] is string -%}
29
+ {{ message['content'] | trim }}
30
+ {%- elif message['content'] is iterable -%}
31
+ {%- for item in message['content'] -%}
32
+ {%- if item['type'] == 'image' -%}
33
+ {{ '<start_of_image>' }}
34
+ {%- elif item['type'] == 'text' -%}
35
+ {{ item['text'] | trim }}
36
+ {%- endif -%}
37
+ {%- endfor -%}
38
+ {%- else -%}
39
+ {{ raise_exception("Invalid content type") }}
40
+ {%- endif -%}
41
+ {{ '<end_of_turn>
42
+ ' }}
43
+ {%- endfor -%}
44
+ {%- if add_generation_prompt -%}
45
+ {{'<start_of_turn>model
46
+ '}}
47
+ {%- endif -%}
2.7_cxr_special/adapters/cxr_specialist/preprocessor_config.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "do_convert_rgb": null,
3
+ "do_normalize": true,
4
+ "do_pan_and_scan": false,
5
+ "do_rescale": true,
6
+ "do_resize": true,
7
+ "image_mean": [
8
+ 0.5,
9
+ 0.5,
10
+ 0.5
11
+ ],
12
+ "image_processor_type": "Gemma3ImageProcessor",
13
+ "image_seq_length": 256,
14
+ "image_std": [
15
+ 0.5,
16
+ 0.5,
17
+ 0.5
18
+ ],
19
+ "pan_and_scan_max_num_crops": null,
20
+ "pan_and_scan_min_crop_size": null,
21
+ "pan_and_scan_min_ratio_to_activate": null,
22
+ "processor_class": "Gemma3Processor",
23
+ "resample": 2,
24
+ "rescale_factor": 0.00392156862745098,
25
+ "size": {
26
+ "height": 896,
27
+ "width": 896
28
+ }
29
+ }
2.7_cxr_special/adapters/cxr_specialist/processor_config.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "image_seq_length": 256,
3
+ "processor_class": "Gemma3Processor"
4
+ }
2.7_cxr_special/adapters/cxr_specialist/projector_adapter.json ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ {
2
+ "rank": 4,
3
+ "alpha": 8.0,
4
+ "dropout": 0.05,
5
+ "dora": true,
6
+ "n_params": 17408
7
+ }
2.7_cxr_special/adapters/cxr_specialist/projector_adapter.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:38fb63a238ad4627abfc12c365ddb7c50f213d2b13c8a89a2b52d6c88de2442a
3
+ size 71386
2.7_cxr_special/adapters/cxr_specialist/special_tokens_map.json ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "boi_token": "<start_of_image>",
3
+ "bos_token": {
4
+ "content": "<bos>",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
8
+ "single_word": false
9
+ },
10
+ "eoi_token": "<end_of_image>",
11
+ "eos_token": {
12
+ "content": "<eos>",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false
17
+ },
18
+ "image_token": "<image_soft_token>",
19
+ "pad_token": {
20
+ "content": "<pad>",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false
25
+ },
26
+ "unk_token": {
27
+ "content": "<unk>",
28
+ "lstrip": false,
29
+ "normalized": false,
30
+ "rstrip": false,
31
+ "single_word": false
32
+ }
33
+ }
2.7_cxr_special/adapters/cxr_specialist/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4667f2089529e8e7657cfb6d1c19910ae71ff5f28aa7ab2ff2763330affad795
3
+ size 33384568
2.7_cxr_special/adapters/cxr_specialist/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1299c11d7cf632ef3b4e11937501358ada021bbdf7c47638d13c0ee982f2e79c
3
+ size 4689074
2.7_cxr_special/adapters/cxr_specialist/tokenizer_config.json ADDED
The diff for this file is too large to render. See raw diff
 
2.7_cxr_special/adapters/cxr_specialist/train_stats.json ADDED
@@ -0,0 +1,79 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arm_id": "cxr_specialist",
3
+ "name": "CXR Specialist (QDoRA r4: ViT nửa sau + projector + decoder all-linear)",
4
+ "trainable_params": 9016832,
5
+ "all_params": 2499239792,
6
+ "alpha": 8,
7
+ "rank": 4,
8
+ "method": "qdora",
9
+ "n_target_modules": 290,
10
+ "projector_adapter": {
11
+ "rank": 4,
12
+ "alpha": 8.0,
13
+ "dropout": 0.05,
14
+ "dora": true,
15
+ "n_params": 17408
16
+ },
17
+ "n_train": 152917,
18
+ "n_stream_failed": 0,
19
+ "n_train_split": 152917,
20
+ "n_no_image": 0,
21
+ "order_sha256": "4a6b4afd45df4b8747700057e8966df69ff7decdd9989731a8b659f288fe8453",
22
+ "phase": "",
23
+ "data_offset": 0,
24
+ "plan": {
25
+ "steps": 200,
26
+ "eff_bs": 32,
27
+ "offset": 0,
28
+ "n_samples": 6400,
29
+ "window": [
30
+ 0,
31
+ 6400
32
+ ],
33
+ "wraps": false,
34
+ "warmup_steps": 20,
35
+ "peak_step": 20,
36
+ "anneal_steps": 180,
37
+ "remaining_after": 146517,
38
+ "phase": "",
39
+ "init_from": null,
40
+ "old_phase": null
41
+ },
42
+ "warm_start_from": null,
43
+ "streaming": true,
44
+ "sampling": "random_without_replacement",
45
+ "trainable_by_area": {
46
+ "vision": 539136,
47
+ "decoder": 8460288,
48
+ "projector": 17408,
49
+ "other": 0
50
+ },
51
+ "steps": 200,
52
+ "batch_size": 4,
53
+ "grad_accum": 8,
54
+ "effective_batch": 32,
55
+ "resumed_from_step": 0,
56
+ "image_max_side": 512,
57
+ "do_pan_and_scan": false,
58
+ "processor_size": 896,
59
+ "schedule": {
60
+ "impl": "explicit",
61
+ "lr_init": 0.0,
62
+ "max_lr": "1e-4",
63
+ "lr_min": "5e-6",
64
+ "pct_start": 0.1,
65
+ "anneal": "cos",
66
+ "steps": 200
67
+ },
68
+ "weight_decay": 0.03,
69
+ "betas": [
70
+ 0.9,
71
+ 0.95
72
+ ],
73
+ "train_loss": 13.871954040527344,
74
+ "minutes": 101.4,
75
+ "vram_peak_gb": 22.28,
76
+ "quantized": true,
77
+ "dora": true,
78
+ "seed": 42
79
+ }