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--- |
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library_name: transformers |
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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: xlsr-nm-nomimo |
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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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# xlsr-nm-nomimo |
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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 the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5614 |
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- Wer: 0.3823 |
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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: 0.0004 |
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- train_batch_size: 8 |
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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: 16 |
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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_steps: 132 |
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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 | |
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|:-------------:|:-------:|:----:|:---------------:|:------:| |
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| 4.9221 | 4.3478 | 200 | 3.0837 | 1.0 | |
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| 3.0104 | 8.6957 | 400 | 2.8149 | 1.0 | |
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| 2.6446 | 13.0435 | 600 | 2.2163 | 1.0 | |
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| 1.605 | 17.3913 | 800 | 0.9394 | 0.7108 | |
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| 0.6986 | 21.7391 | 1000 | 0.7128 | 0.5799 | |
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| 0.3653 | 26.0870 | 1200 | 0.5925 | 0.4724 | |
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| 0.2403 | 30.4348 | 1400 | 0.6623 | 0.4884 | |
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| 0.1829 | 34.7826 | 1600 | 0.6467 | 0.4564 | |
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| 0.1415 | 39.1304 | 1800 | 0.6584 | 0.4462 | |
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| 0.1127 | 43.4783 | 2000 | 0.6751 | 0.4462 | |
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| 0.0977 | 47.8261 | 2200 | 0.6630 | 0.4142 | |
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| 0.0794 | 52.1739 | 2400 | 0.5528 | 0.4230 | |
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| 0.0733 | 56.5217 | 2600 | 0.5641 | 0.4041 | |
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| 0.0574 | 60.8696 | 2800 | 0.6927 | 0.4012 | |
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| 0.0518 | 65.2174 | 3000 | 0.6562 | 0.3983 | |
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| 0.0375 | 69.5652 | 3200 | 0.6104 | 0.3852 | |
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| 0.0352 | 73.9130 | 3400 | 0.5976 | 0.3852 | |
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| 0.0297 | 78.2609 | 3600 | 0.6563 | 0.3852 | |
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| 0.0268 | 82.6087 | 3800 | 0.5655 | 0.3706 | |
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| 0.0225 | 86.9565 | 4000 | 0.6450 | 0.3823 | |
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| 0.0213 | 91.3043 | 4200 | 0.6029 | 0.3837 | |
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| 0.017 | 95.6522 | 4400 | 0.5496 | 0.3808 | |
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| 0.0166 | 100.0 | 4600 | 0.5614 | 0.3823 | |
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### Framework versions |
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- Transformers 4.47.0.dev0 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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