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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: cmb-20s_asr-scr_w2v2-base_002 |
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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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# cmb-20s_asr-scr_w2v2-base_002 |
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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: 0.2887 |
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- Per: 0.1279 |
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- Pcc: 0.6501 |
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- Ctc Loss: 0.3968 |
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- Mse Loss: 1.0164 |
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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: 8928 |
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- training_steps: 89280 |
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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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| 11.516 | 3.0 | 8928 | 4.4204 | 0.9956 | 0.6302 | 3.7718 | 0.8695 | |
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| 2.6821 | 6.0 | 17856 | 1.4363 | 0.1800 | 0.6754 | 0.6151 | 0.8033 | |
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| 1.0205 | 9.0 | 26784 | 1.4608 | 0.1457 | 0.6734 | 0.4819 | 0.9911 | |
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| 0.5238 | 12.0 | 35712 | 1.1546 | 0.1375 | 0.6624 | 0.4382 | 0.8751 | |
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| 0.0849 | 15.0 | 44640 | 1.2248 | 0.1338 | 0.6576 | 0.4181 | 1.0163 | |
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| -0.3644 | 18.0 | 53568 | 1.4907 | 0.1314 | 0.6513 | 0.4077 | 1.2464 | |
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| -0.8166 | 21.0 | 62496 | 0.5897 | 0.1302 | 0.6518 | 0.4054 | 0.8912 | |
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| -1.2642 | 24.0 | 71424 | 0.5638 | 0.1286 | 0.6511 | 0.3985 | 0.9995 | |
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| -1.6765 | 27.0 | 80352 | 0.4494 | 0.1282 | 0.6490 | 0.3980 | 1.0442 | |
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| -1.9395 | 30.0 | 89280 | 0.2887 | 0.1279 | 0.6501 | 0.3968 | 1.0164 | |
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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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