Instructions to use T0KII/MASRIBERTv3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use T0KII/MASRIBERTv3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="T0KII/MASRIBERTv3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("T0KII/MASRIBERTv3") model = AutoModelForMaskedLM.from_pretrained("T0KII/MASRIBERTv3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 4000, checkpoint
Browse files
last-checkpoint/model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 775678032
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ea56500a65560a074ca9ab85e6281dce5baca5e2f1336bc9ca93232b5bc89d90
|
| 3 |
size 775678032
|
last-checkpoint/optimizer.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1551478091
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:024a31d59f0cff6c5d0a6d61ae47e324de8a830ee1fbf5280bb6cfc82d5516a9
|
| 3 |
size 1551478091
|
last-checkpoint/rng_state.pth
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 14645
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:aa2b146bcd369b1d02f52100689733e474ff192ab87af4ee028609a153d47508
|
| 3 |
size 14645
|
last-checkpoint/scaler.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1383
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c0033c7745b46bdca3ecab5787678834ca68f7f7e1288869dceeb38812abc253
|
| 3 |
size 1383
|
last-checkpoint/scheduler.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1465
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3f7d02a0acf38a2c254c6270baa35a3c72938f51148a14bde80f5a273d0fc711
|
| 3 |
size 1465
|
last-checkpoint/trainer_state.json
CHANGED
|
@@ -1,10 +1,10 @@
|
|
| 1 |
{
|
| 2 |
-
"best_global_step":
|
| 3 |
-
"best_metric": 5.
|
| 4 |
-
"best_model_checkpoint": "/kaggle/working/MASRIBERTv3_ckpts/checkpoint-
|
| 5 |
-
"epoch": 0.
|
| 6 |
"eval_steps": 1000,
|
| 7 |
-
"global_step":
|
| 8 |
"is_hyper_param_search": false,
|
| 9 |
"is_local_process_zero": true,
|
| 10 |
"is_world_process_zero": true,
|
|
@@ -116,6 +116,42 @@
|
|
| 116 |
"eval_samples_per_second": 70.091,
|
| 117 |
"eval_steps_per_second": 1.096,
|
| 118 |
"step": 3000
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 119 |
}
|
| 120 |
],
|
| 121 |
"logging_steps": 250,
|
|
@@ -144,7 +180,7 @@
|
|
| 144 |
"attributes": {}
|
| 145 |
}
|
| 146 |
},
|
| 147 |
-
"total_flos":
|
| 148 |
"train_batch_size": 32,
|
| 149 |
"trial_name": null,
|
| 150 |
"trial_params": null
|
|
|
|
| 1 |
{
|
| 2 |
+
"best_global_step": 4000,
|
| 3 |
+
"best_metric": 5.337510108947754,
|
| 4 |
+
"best_model_checkpoint": "/kaggle/working/MASRIBERTv3_ckpts/checkpoint-4000",
|
| 5 |
+
"epoch": 0.6013003119245368,
|
| 6 |
"eval_steps": 1000,
|
| 7 |
+
"global_step": 4000,
|
| 8 |
"is_hyper_param_search": false,
|
| 9 |
"is_local_process_zero": true,
|
| 10 |
"is_world_process_zero": true,
|
|
|
|
| 116 |
"eval_samples_per_second": 70.091,
|
| 117 |
"eval_steps_per_second": 1.096,
|
| 118 |
"step": 3000
|
| 119 |
+
},
|
| 120 |
+
{
|
| 121 |
+
"epoch": 0.4885565034386862,
|
| 122 |
+
"grad_norm": 100.90162658691406,
|
| 123 |
+
"learning_rate": 4.9925434012594344e-05,
|
| 124 |
+
"loss": 46.94662109375,
|
| 125 |
+
"step": 3250
|
| 126 |
+
},
|
| 127 |
+
{
|
| 128 |
+
"epoch": 0.5261377729339697,
|
| 129 |
+
"grad_norm": 97.686767578125,
|
| 130 |
+
"learning_rate": 4.9848779106991685e-05,
|
| 131 |
+
"loss": 46.1941953125,
|
| 132 |
+
"step": 3500
|
| 133 |
+
},
|
| 134 |
+
{
|
| 135 |
+
"epoch": 0.5637190424292533,
|
| 136 |
+
"grad_norm": 85.13678741455078,
|
| 137 |
+
"learning_rate": 4.974540876095457e-05,
|
| 138 |
+
"loss": 45.45590234375,
|
| 139 |
+
"step": 3750
|
| 140 |
+
},
|
| 141 |
+
{
|
| 142 |
+
"epoch": 0.6013003119245368,
|
| 143 |
+
"grad_norm": 88.05296325683594,
|
| 144 |
+
"learning_rate": 4.9615434110096976e-05,
|
| 145 |
+
"loss": 44.72342578125,
|
| 146 |
+
"step": 4000
|
| 147 |
+
},
|
| 148 |
+
{
|
| 149 |
+
"epoch": 0.6013003119245368,
|
| 150 |
+
"eval_loss": 5.337510108947754,
|
| 151 |
+
"eval_runtime": 245.395,
|
| 152 |
+
"eval_samples_per_second": 70.099,
|
| 153 |
+
"eval_steps_per_second": 1.096,
|
| 154 |
+
"step": 4000
|
| 155 |
}
|
| 156 |
],
|
| 157 |
"logging_steps": 250,
|
|
|
|
| 180 |
"attributes": {}
|
| 181 |
}
|
| 182 |
},
|
| 183 |
+
"total_flos": 6.7466744561664e+16,
|
| 184 |
"train_batch_size": 32,
|
| 185 |
"trial_name": null,
|
| 186 |
"trial_params": null
|