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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: wav2vec2-1 |
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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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# wav2vec2-1 |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5980 |
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- Wer: 0.4949 |
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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: 32 |
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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: 400 |
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- num_epochs: 30 |
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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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| 4.2691 | 1.37 | 200 | 2.9045 | 1.0 | |
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| 1.6356 | 2.74 | 400 | 0.9277 | 0.8678 | |
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| 0.8062 | 4.11 | 600 | 0.8200 | 0.7776 | |
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| 0.5983 | 5.48 | 800 | 0.6829 | 0.7161 | |
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| 0.4863 | 6.85 | 1000 | 0.6205 | 0.6507 | |
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| 0.407 | 8.22 | 1200 | 0.6519 | 0.6763 | |
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| 0.3641 | 9.59 | 1400 | 0.5771 | 0.6088 | |
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| 0.3291 | 10.96 | 1600 | 0.6548 | 0.6202 | |
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| 0.2905 | 12.33 | 1800 | 0.6538 | 0.5828 | |
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| 0.2613 | 13.7 | 2000 | 0.6281 | 0.5864 | |
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| 0.2354 | 15.07 | 2200 | 0.5936 | 0.5630 | |
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| 0.2145 | 16.44 | 2400 | 0.5877 | 0.5699 | |
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| 0.2008 | 17.81 | 2600 | 0.5469 | 0.5488 | |
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| 0.1751 | 19.18 | 2800 | 0.6453 | 0.5584 | |
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| 0.169 | 20.55 | 3000 | 0.5871 | 0.5357 | |
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| 0.1521 | 21.92 | 3200 | 0.6063 | 0.5318 | |
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| 0.1426 | 23.29 | 3400 | 0.5609 | 0.5171 | |
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| 0.1287 | 24.66 | 3600 | 0.6056 | 0.5126 | |
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| 0.1236 | 26.03 | 3800 | 0.5994 | 0.5074 | |
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| 0.1138 | 27.4 | 4000 | 0.5980 | 0.4944 | |
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| 0.1083 | 28.77 | 4200 | 0.5980 | 0.4949 | |
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### Framework versions |
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- Transformers 4.19.2 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.2.2 |
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- Tokenizers 0.12.1 |
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