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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-10hrs-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-10hrs-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: 0.6790 |
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- Wer: 0.2525 |
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- Cer: 0.0897 |
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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: 8 |
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- eval_batch_size: 4 |
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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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| 2.9209 | 1.0 | 710 | 0.9107 | 0.4690 | 0.1399 | |
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| 0.6799 | 2.0 | 1420 | 0.6451 | 0.3166 | 0.1020 | |
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| 0.5118 | 3.0 | 2130 | 0.6325 | 0.2602 | 0.0900 | |
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| 0.4435 | 4.0 | 2840 | 0.5829 | 0.2610 | 0.0951 | |
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| 0.3857 | 5.0 | 3550 | 0.5528 | 0.2585 | 0.0952 | |
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| 0.3363 | 6.0 | 4260 | 0.5604 | 0.2449 | 0.0863 | |
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| 0.3312 | 7.0 | 4970 | 0.6122 | 0.3529 | 0.1307 | |
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| 0.3306 | 8.0 | 5680 | 0.5529 | 0.2572 | 0.0931 | |
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| 0.2915 | 9.0 | 6390 | 0.6499 | 0.2584 | 0.0929 | |
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| 0.2828 | 10.0 | 7100 | 0.6233 | 0.2678 | 0.0954 | |
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| 0.2664 | 11.0 | 7810 | 0.6266 | 0.2567 | 0.0904 | |
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| 0.2473 | 12.0 | 8520 | 0.6285 | 0.2561 | 0.0894 | |
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| 0.2289 | 13.0 | 9230 | 0.6137 | 0.2531 | 0.0901 | |
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| 0.2102 | 14.0 | 9940 | 0.6440 | 0.2483 | 0.0891 | |
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| 0.1976 | 15.0 | 10650 | 0.7161 | 0.2724 | 0.0957 | |
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| 0.1971 | 16.0 | 11360 | 0.6790 | 0.2525 | 0.0897 | |
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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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