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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: pic-20s_asr-scr_w2v2-base_001 |
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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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# pic-20s_asr-scr_w2v2-base_001 |
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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: 1.4443 |
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- Per: 0.1499 |
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- Pcc: 0.6371 |
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- Ctc Loss: 0.5406 |
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- Mse Loss: 0.8841 |
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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: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 1 |
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- seed: 2222 |
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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: 2247 |
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- training_steps: 22470 |
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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 | Per | Pcc | Ctc Loss | Mse Loss | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:| |
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| 16.6841 | 3.0 | 2247 | 4.7118 | 0.9979 | 0.6160 | 3.7745 | 1.0013 | |
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| 4.2857 | 6.0 | 4494 | 4.2485 | 0.9979 | 0.6999 | 3.7428 | 0.6844 | |
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| 3.9118 | 9.0 | 6741 | 4.2032 | 0.9979 | 0.6863 | 3.7209 | 0.7501 | |
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| 3.5336 | 12.0 | 8988 | 3.8740 | 0.9976 | 0.6645 | 3.1591 | 0.9697 | |
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| 2.1131 | 15.0 | 11235 | 2.0043 | 0.2726 | 0.6564 | 1.1426 | 0.8936 | |
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| 0.9858 | 18.0 | 13482 | 1.6048 | 0.1817 | 0.6377 | 0.7083 | 0.8783 | |
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| 0.7106 | 21.0 | 15729 | 1.5797 | 0.1625 | 0.6447 | 0.6061 | 0.9394 | |
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| 0.5928 | 24.0 | 17976 | 1.4856 | 0.1552 | 0.6392 | 0.5624 | 0.8977 | |
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| 0.525 | 27.0 | 20223 | 1.4673 | 0.1515 | 0.6343 | 0.5471 | 0.8972 | |
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| 0.4862 | 30.0 | 22470 | 1.4443 | 0.1499 | 0.6371 | 0.5406 | 0.8841 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.0.1 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.2 |
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