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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: XLS-R_53_english |
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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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# XLS-R_53_english |
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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: 0.3430 |
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- Wer: 0.3033 |
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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: 0.0001 |
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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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- 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: 1000 |
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- num_epochs: 30 |
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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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| 4.6589 | 1.65 | 500 | 3.1548 | 1.0 | |
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| 2.5363 | 3.3 | 1000 | 1.0250 | 0.8707 | |
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| 0.849 | 4.95 | 1500 | 0.3964 | 0.4636 | |
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| 0.4812 | 6.6 | 2000 | 0.3341 | 0.3907 | |
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| 0.3471 | 8.25 | 2500 | 0.3351 | 0.3659 | |
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| 0.2797 | 9.9 | 3000 | 0.3104 | 0.3475 | |
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| 0.2336 | 11.55 | 3500 | 0.3545 | 0.3419 | |
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| 0.2116 | 13.2 | 4000 | 0.3577 | 0.3353 | |
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| 0.1688 | 14.85 | 4500 | 0.3383 | 0.3302 | |
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| 0.1587 | 16.5 | 5000 | 0.3431 | 0.3235 | |
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| 0.1358 | 18.15 | 5500 | 0.3504 | 0.3209 | |
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| 0.1323 | 19.8 | 6000 | 0.3468 | 0.3191 | |
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| 0.115 | 21.45 | 6500 | 0.3331 | 0.3127 | |
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| 0.108 | 23.1 | 7000 | 0.3497 | 0.3099 | |
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| 0.0938 | 24.75 | 7500 | 0.3532 | 0.3091 | |
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| 0.0974 | 26.4 | 8000 | 0.3461 | 0.3086 | |
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| 0.0867 | 28.05 | 8500 | 0.3422 | 0.3054 | |
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| 0.0852 | 29.7 | 9000 | 0.3430 | 0.3033 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 1.18.3 |
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- Tokenizers 0.12.1 |
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