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--- |
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library_name: transformers |
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license: mit |
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base_model: facebook/w2v-bert-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_11_0 |
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metrics: |
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- wer |
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- bleu |
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model-index: |
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- name: w2v3 |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: common_voice_11_0 |
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type: common_voice_11_0 |
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config: ar |
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split: test |
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args: ar |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.14435763249060218 |
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- name: Bleu |
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type: bleu |
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value: 0.625443124553845 |
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--- |
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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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# w2v3 |
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_11_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1747 |
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- Wer: 0.1444 |
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- Cer: 0.0349 |
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- Bleu: 0.6254 |
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- Bert Score F1: 0.9721 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- training_steps: 5000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Bleu | Bert Score F1 | |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:-------------:| |
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| 0.3995 | 0.0357 | 250 | 0.3664 | 0.2725 | 0.0732 | 0.4414 | 0.9332 | |
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| 0.3065 | 0.0713 | 500 | 0.3399 | 0.2119 | 0.0593 | 0.5188 | 0.9465 | |
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| 0.2648 | 0.1070 | 750 | 0.3095 | 0.2327 | 0.0633 | 0.4970 | 0.9430 | |
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| 0.2393 | 0.1426 | 1000 | 0.2885 | 0.2134 | 0.0551 | 0.5156 | 0.9545 | |
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| 0.2756 | 0.1783 | 1250 | 0.2486 | 0.1817 | 0.0467 | 0.5670 | 0.9614 | |
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| 0.2005 | 0.2139 | 1500 | 0.2448 | 0.1935 | 0.0482 | 0.5485 | 0.9588 | |
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| 0.2112 | 0.2496 | 1750 | 0.2377 | 0.1823 | 0.0464 | 0.5617 | 0.9622 | |
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| 0.1934 | 0.2853 | 2000 | 0.2226 | 0.1674 | 0.0420 | 0.5888 | 0.9658 | |
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| 0.1631 | 0.3209 | 2250 | 0.2205 | 0.1660 | 0.0421 | 0.5888 | 0.9647 | |
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| 0.1905 | 0.3566 | 2500 | 0.2249 | 0.1679 | 0.0429 | 0.5879 | 0.9651 | |
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| 0.1639 | 0.3922 | 2750 | 0.2026 | 0.1625 | 0.0403 | 0.5975 | 0.9673 | |
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| 0.1567 | 0.4279 | 3000 | 0.1895 | 0.1516 | 0.0379 | 0.6150 | 0.9685 | |
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| 0.1641 | 0.4636 | 3250 | 0.1984 | 0.1555 | 0.0379 | 0.6076 | 0.9693 | |
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| 0.1404 | 0.4992 | 3500 | 0.1876 | 0.1528 | 0.0370 | 0.6124 | 0.9696 | |
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| 0.1475 | 0.5349 | 3750 | 0.1913 | 0.1568 | 0.0381 | 0.6055 | 0.9691 | |
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| 0.1586 | 0.5705 | 4000 | 0.1846 | 0.1510 | 0.0366 | 0.6151 | 0.9705 | |
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| 0.1322 | 0.6062 | 4250 | 0.1801 | 0.1475 | 0.0356 | 0.6208 | 0.9715 | |
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| 0.1396 | 0.6418 | 4500 | 0.1788 | 0.1454 | 0.0351 | 0.6242 | 0.9720 | |
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| 0.1287 | 0.6775 | 4750 | 0.1755 | 0.1455 | 0.0352 | 0.6233 | 0.9718 | |
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| 0.1376 | 0.7132 | 5000 | 0.1747 | 0.1444 | 0.0349 | 0.6254 | 0.9721 | |
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### Framework versions |
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- Transformers 4.50.0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.3.1 |
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- Tokenizers 0.21.0 |
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