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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: saq-20s_asr-scr_w2v2-base_003 |
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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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# saq-20s_asr-scr_w2v2-base_003 |
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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: 1.4770 |
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- Per: 0.1582 |
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- Pcc: 0.6742 |
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- Ctc Loss: 0.5610 |
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- Mse Loss: 0.8995 |
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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: 3333 |
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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: 2226 |
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- training_steps: 22260 |
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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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| 16.8423 | 3.0 | 2226 | 4.5928 | 0.9983 | 0.6376 | 3.7671 | 0.8900 | |
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| 4.329 | 6.0 | 4452 | 4.5763 | 0.9983 | 0.6939 | 3.7500 | 0.9944 | |
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| 3.9518 | 9.0 | 6678 | 4.3570 | 0.9983 | 0.6962 | 3.7043 | 0.9024 | |
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| 3.4509 | 12.0 | 8904 | 3.2020 | 0.8036 | 0.6831 | 2.6097 | 0.7935 | |
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| 1.6554 | 15.0 | 11130 | 1.7792 | 0.2361 | 0.6712 | 0.9476 | 0.8436 | |
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| 0.9205 | 18.0 | 13356 | 1.6586 | 0.1900 | 0.6858 | 0.7026 | 0.9314 | |
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| 0.7081 | 21.0 | 15582 | 1.5955 | 0.1721 | 0.6716 | 0.6236 | 0.9429 | |
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| 0.5965 | 24.0 | 17808 | 1.5239 | 0.1634 | 0.6784 | 0.5880 | 0.9140 | |
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| 0.5351 | 27.0 | 20034 | 1.4992 | 0.1595 | 0.6782 | 0.5682 | 0.9115 | |
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| 0.5012 | 30.0 | 22260 | 1.4770 | 0.1582 | 0.6742 | 0.5610 | 0.8995 | |
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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 2.18.0 |
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- Tokenizers 0.15.2 |
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