sulaimank
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w2v-bert-grain-lg_grn_only

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 ---
 library_name: transformers
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 ---
 library_name: transformers
+license: mit
+base_model: facebook/w2v-bert-2.0
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: w2v-bert-grain-lg_grn_only
+  results: []
 ---
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+# w2v-bert-grain-lg_grn_only
+This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1053
+- Wer: 0.0336
+- Cer: 0.0113
+## Model description
+More information needed
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+More information needed
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 100
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
+| 0.992         | 1.0   | 482   | 0.1349          | 0.1317 | 0.0273 |
+| 0.178         | 2.0   | 964   | 0.1184          | 0.0983 | 0.0213 |
+| 0.12          | 3.0   | 1446  | 0.1047          | 0.0833 | 0.0185 |
+| 0.091         | 4.0   | 1928  | 0.0996          | 0.0742 | 0.0175 |
+| 0.0721        | 5.0   | 2410  | 0.0946          | 0.0712 | 0.0175 |
+| 0.0593        | 6.0   | 2892  | 0.1013          | 0.0686 | 0.0168 |
+| 0.0479        | 7.0   | 3374  | 0.0908          | 0.0614 | 0.0148 |
+| 0.0421        | 8.0   | 3856  | 0.0956          | 0.0649 | 0.0159 |
+| 0.0371        | 9.0   | 4338  | 0.1026          | 0.0694 | 0.0170 |
+| 0.0328        | 10.0  | 4820  | 0.1046          | 0.0592 | 0.0145 |
+| 0.031         | 11.0  | 5302  | 0.0912          | 0.0529 | 0.0134 |
+| 0.0255        | 12.0  | 5784  | 0.0870          | 0.0547 | 0.0140 |
+| 0.0224        | 13.0  | 6266  | 0.1073          | 0.0588 | 0.0146 |
+| 0.0207        | 14.0  | 6748  | 0.0963          | 0.0493 | 0.0136 |
+| 0.0212        | 15.0  | 7230  | 0.1016          | 0.0484 | 0.0149 |
+| 0.0183        | 16.0  | 7712  | 0.0994          | 0.0456 | 0.0125 |
+| 0.0185        | 17.0  | 8194  | 0.1107          | 0.0495 | 0.0134 |
+| 0.0181        | 18.0  | 8676  | 0.1012          | 0.0482 | 0.0136 |
+| 0.0153        | 19.0  | 9158  | 0.0947          | 0.0506 | 0.0140 |
+| 0.0131        | 20.0  | 9640  | 0.0890          | 0.0475 | 0.0121 |
+| 0.0113        | 21.0  | 10122 | 0.0884          | 0.0475 | 0.0126 |
+| 0.0114        | 22.0  | 10604 | 0.1205          | 0.0597 | 0.0147 |
+| 0.0117        | 23.0  | 11086 | 0.0864          | 0.0404 | 0.0111 |
+| 0.0107        | 24.0  | 11568 | 0.0939          | 0.0401 | 0.0122 |
+| 0.0094        | 25.0  | 12050 | 0.0997          | 0.0404 | 0.0119 |
+| 0.0078        | 26.0  | 12532 | 0.0952          | 0.0399 | 0.0121 |
+| 0.0088        | 27.0  | 13014 | 0.1014          | 0.0417 | 0.0116 |
+| 0.0077        | 28.0  | 13496 | 0.0954          | 0.0380 | 0.0110 |
+| 0.0072        | 29.0  | 13978 | 0.1035          | 0.0427 | 0.0124 |
+| 0.0084        | 30.0  | 14460 | 0.0977          | 0.0401 | 0.0119 |
+| 0.0082        | 31.0  | 14942 | 0.0929          | 0.0378 | 0.0117 |
+| 0.0084        | 32.0  | 15424 | 0.0966          | 0.0397 | 0.0119 |
+| 0.0055        | 33.0  | 15906 | 0.0967          | 0.0401 | 0.0115 |
+| 0.006         | 34.0  | 16388 | 0.0899          | 0.0354 | 0.0107 |
+| 0.006         | 35.0  | 16870 | 0.0954          | 0.0351 | 0.0107 |
+| 0.0049        | 36.0  | 17352 | 0.0988          | 0.0484 | 0.0128 |
+| 0.0073        | 37.0  | 17834 | 0.0947          | 0.0349 | 0.0107 |
+| 0.0049        | 38.0  | 18316 | 0.0893          | 0.0343 | 0.0104 |
+| 0.0036        | 39.0  | 18798 | 0.0909          | 0.0317 | 0.0097 |
+| 0.0049        | 40.0  | 19280 | 0.0875          | 0.0328 | 0.0099 |
+| 0.0061        | 41.0  | 19762 | 0.1071          | 0.0371 | 0.0114 |
+| 0.0059        | 42.0  | 20244 | 0.0979          | 0.0380 | 0.0114 |
+| 0.0043        | 43.0  | 20726 | 0.0914          | 0.0347 | 0.0102 |
+| 0.0034        | 44.0  | 21208 | 0.0946          | 0.0321 | 0.0100 |
+| 0.004         | 45.0  | 21690 | 0.0905          | 0.0338 | 0.0097 |
+| 0.0038        | 46.0  | 22172 | 0.0967          | 0.0312 | 0.0104 |
+| 0.0023        | 47.0  | 22654 | 0.0986          | 0.0336 | 0.0104 |
+| 0.0025        | 48.0  | 23136 | 0.0873          | 0.0299 | 0.0095 |
+| 0.0027        | 49.0  | 23618 | 0.1071          | 0.0349 | 0.0111 |
+| 0.003         | 50.0  | 24100 | 0.0968          | 0.0293 | 0.0098 |
+| 0.0033        | 51.0  | 24582 | 0.1058          | 0.0404 | 0.0120 |
+| 0.0034        | 52.0  | 25064 | 0.1020          | 0.0367 | 0.0113 |
+| 0.0031        | 53.0  | 25546 | 0.0950          | 0.0302 | 0.0093 |
+| 0.0016        | 54.0  | 26028 | 0.0988          | 0.0315 | 0.0100 |
+| 0.0027        | 55.0  | 26510 | 0.0868          | 0.0297 | 0.0096 |
+| 0.003         | 56.0  | 26992 | 0.0955          | 0.0332 | 0.0103 |
+| 0.002         | 57.0  | 27474 | 0.0930          | 0.0315 | 0.0102 |
+| 0.0022        | 58.0  | 27956 | 0.1053          | 0.0336 | 0.0113 |
+### Framework versions
+- Transformers 4.46.1
+- Pytorch 2.1.0+cu118
+- Datasets 3.1.0
+- Tokenizers 0.20.1

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