Instructions to use Shaer-AI/ARBERT-base-submeter-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shaer-AI/ARBERT-base-submeter-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Shaer-AI/ARBERT-base-submeter-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Shaer-AI/ARBERT-base-submeter-classifier") model = AutoModelForSequenceClassification.from_pretrained("Shaer-AI/ARBERT-base-submeter-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 12000, 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 651465828
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1480d9f4a630f6362b6c9b9468cf771d2a85b6a789312d734a4392acf6401523
|
| 3 |
size 651465828
|
last-checkpoint/optimizer.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1303053067
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c2281b994c226e57b66b8d419588cdcb42cbd3535018df591d44d76344dea3b7
|
| 3 |
size 1303053067
|
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:f3e8edef986f4bbf76f2de5f38080bedbaeda32f953eac6bedda8cf73cae1fd6
|
| 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:ae029a8e6af9f014c9ef8b713fcd28cef1f184648ddde977ce75efc89ca9a242
|
| 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 sha256:7d447d717c68fd522f6372d2b3ebbc9666da3ac61bf609597ba0f72b0cdaf7a6
|
| 3 |
size 1465
|
last-checkpoint/trainer_state.json
CHANGED
|
@@ -1,10 +1,10 @@
|
|
| 1 |
{
|
| 2 |
-
"best_global_step":
|
| 3 |
-
"best_metric": 0.
|
| 4 |
-
"best_model_checkpoint": "/kaggle/working/arbert_submeter_training/checkpoints/checkpoint-
|
| 5 |
-
"epoch":
|
| 6 |
"eval_steps": 500,
|
| 7 |
-
"global_step":
|
| 8 |
"is_hyper_param_search": false,
|
| 9 |
"is_local_process_zero": true,
|
| 10 |
"is_world_process_zero": true,
|
|
@@ -422,6 +422,24 @@
|
|
| 422 |
"eval_steps_per_second": 3.448,
|
| 423 |
"eval_weighted_f1": 0.9623140045622489,
|
| 424 |
"step": 11500
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 425 |
}
|
| 426 |
],
|
| 427 |
"logging_steps": 500,
|
|
@@ -441,7 +459,7 @@
|
|
| 441 |
"attributes": {}
|
| 442 |
}
|
| 443 |
},
|
| 444 |
-
"total_flos":
|
| 445 |
"train_batch_size": 128,
|
| 446 |
"trial_name": null,
|
| 447 |
"trial_params": null
|
|
|
|
| 1 |
{
|
| 2 |
+
"best_global_step": 12000,
|
| 3 |
+
"best_metric": 0.9689324324324324,
|
| 4 |
+
"best_model_checkpoint": "/kaggle/working/arbert_submeter_training/checkpoints/checkpoint-12000",
|
| 5 |
+
"epoch": 2.0754129551154543,
|
| 6 |
"eval_steps": 500,
|
| 7 |
+
"global_step": 12000,
|
| 8 |
"is_hyper_param_search": false,
|
| 9 |
"is_local_process_zero": true,
|
| 10 |
"is_world_process_zero": true,
|
|
|
|
| 422 |
"eval_steps_per_second": 3.448,
|
| 423 |
"eval_weighted_f1": 0.9623140045622489,
|
| 424 |
"step": 11500
|
| 425 |
+
},
|
| 426 |
+
{
|
| 427 |
+
"epoch": 2.0754129551154543,
|
| 428 |
+
"grad_norm": 3.1163055896759033,
|
| 429 |
+
"learning_rate": 1.5412775279603368e-05,
|
| 430 |
+
"loss": 0.0899,
|
| 431 |
+
"step": 12000
|
| 432 |
+
},
|
| 433 |
+
{
|
| 434 |
+
"epoch": 2.0754129551154543,
|
| 435 |
+
"eval_accuracy": 0.9689324324324324,
|
| 436 |
+
"eval_loss": 0.11741844564676285,
|
| 437 |
+
"eval_macro_f1": 0.5972224837605217,
|
| 438 |
+
"eval_runtime": 419.245,
|
| 439 |
+
"eval_samples_per_second": 882.539,
|
| 440 |
+
"eval_steps_per_second": 3.449,
|
| 441 |
+
"eval_weighted_f1": 0.9632448268921581,
|
| 442 |
+
"step": 12000
|
| 443 |
}
|
| 444 |
],
|
| 445 |
"logging_steps": 500,
|
|
|
|
| 459 |
"attributes": {}
|
| 460 |
}
|
| 461 |
},
|
| 462 |
+
"total_flos": 5.052137308550477e+16,
|
| 463 |
"train_batch_size": 128,
|
| 464 |
"trial_name": null,
|
| 465 |
"trial_params": null
|