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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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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: wav2vec2_l2arctic |
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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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# wav2vec2_l2arctic |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co./facebook/wav2vec2-large-xlsr-53) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5487 |
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- Wer: 0.1460 |
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- Cer: 0.0904 |
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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: 0.0003 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 20 |
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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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| 6.3356 | 0.9941 | 84 | 4.6295 | 1.0 | 1.0 | |
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| 3.5484 | 2.0 | 169 | 3.5272 | 1.0 | 1.0 | |
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| 3.5314 | 2.9941 | 253 | 3.5110 | 1.0 | 1.0 | |
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| 3.5084 | 4.0 | 338 | 3.5019 | 1.0 | 1.0 | |
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| 3.3271 | 4.9941 | 422 | 3.2417 | 1.0 | 1.0 | |
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| 1.6302 | 6.0 | 507 | 1.0777 | 0.3444 | 0.3220 | |
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| 0.7834 | 6.9941 | 591 | 0.6123 | 0.1780 | 0.1189 | |
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| 0.6067 | 8.0 | 676 | 0.5169 | 0.1550 | 0.0983 | |
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| 0.534 | 8.9941 | 760 | 0.5095 | 0.1549 | 0.0993 | |
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| 0.4711 | 10.0 | 845 | 0.4976 | 0.1524 | 0.0962 | |
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| 0.3979 | 10.9941 | 929 | 0.4951 | 0.1497 | 0.0937 | |
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| 0.354 | 12.0 | 1014 | 0.5012 | 0.1505 | 0.0943 | |
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| 0.3415 | 12.9941 | 1098 | 0.5090 | 0.1489 | 0.0937 | |
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| 0.295 | 14.0 | 1183 | 0.5098 | 0.1488 | 0.0944 | |
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| 0.2917 | 14.9941 | 1267 | 0.5296 | 0.1507 | 0.0946 | |
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| 0.2397 | 16.0 | 1352 | 0.5315 | 0.1507 | 0.0944 | |
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| 0.2713 | 16.9941 | 1436 | 0.5367 | 0.1467 | 0.0913 | |
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| 0.2153 | 18.0 | 1521 | 0.5456 | 0.1483 | 0.0924 | |
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| 0.206 | 18.9941 | 1605 | 0.5464 | 0.1471 | 0.0914 | |
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| 0.2488 | 19.8817 | 1680 | 0.5487 | 0.1460 | 0.0904 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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