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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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metrics: |
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- wer |
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model-index: |
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- name: w2v-bert-2.0-CV_Fleurs_AMMI_ALFFA-sw-20hrs-v1 |
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results: [] |
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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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# w2v-bert-2.0-CV_Fleurs_AMMI_ALFFA-sw-20hrs-v1 |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5645 |
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- Wer: 0.2500 |
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- Cer: 0.0899 |
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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: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 2 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 100 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| |
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| 1.7972 | 1.0 | 2970 | 0.6806 | 0.2849 | 0.0958 | |
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| 0.4586 | 2.0 | 5940 | 0.6101 | 0.2595 | 0.0922 | |
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| 0.3832 | 3.0 | 8910 | 0.5412 | 0.2290 | 0.0789 | |
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| 0.3513 | 4.0 | 11880 | 0.4830 | 0.2379 | 0.0865 | |
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| 0.3284 | 5.0 | 14850 | 0.5698 | 0.2259 | 0.0800 | |
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| 0.3268 | 6.0 | 17820 | 0.6145 | 0.2308 | 0.0810 | |
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| 0.3129 | 7.0 | 20790 | 0.5390 | 0.2517 | 0.0883 | |
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| 0.2935 | 8.0 | 23760 | 0.6146 | 0.2366 | 0.0858 | |
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| 0.2829 | 9.0 | 26730 | 0.6222 | 0.2571 | 0.0892 | |
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| 0.2835 | 10.0 | 29700 | 0.6284 | 0.2480 | 0.0907 | |
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| 0.2709 | 11.0 | 32670 | 0.6553 | 0.2542 | 0.0923 | |
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| 0.2468 | 12.0 | 35640 | 0.6046 | 0.2406 | 0.0868 | |
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| 0.2337 | 13.0 | 38610 | 0.6232 | 0.2411 | 0.0880 | |
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| 0.2037 | 14.0 | 41580 | 0.6318 | 0.2290 | 0.0837 | |
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| 0.2021 | 15.0 | 44550 | 0.5645 | 0.2500 | 0.0899 | |
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### Framework versions |
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- Transformers 4.46.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.0.2 |
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- Tokenizers 0.20.1 |
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