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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: k2e-20s_asr-scr_w2v2-large_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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# k2e-20s_asr-scr_w2v2-large_001 |
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This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7509 |
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- Per: 0.1453 |
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- Pcc: 0.6324 |
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- Ctc Loss: 0.5111 |
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- Mse Loss: 1.2263 |
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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: 1111 |
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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: 2235 |
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- training_steps: 22350 |
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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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| 14.3265 | 3.0 | 2235 | 4.6461 | 0.9890 | 0.6160 | 3.6176 | 1.0856 | |
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| 3.4446 | 6.01 | 4470 | 2.8757 | 0.3498 | 0.6516 | 1.0729 | 1.7895 | |
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| 1.5549 | 9.01 | 6705 | 2.0517 | 0.1846 | 0.6507 | 0.6672 | 1.3503 | |
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| 1.1194 | 12.02 | 8940 | 1.8625 | 0.1650 | 0.6443 | 0.5914 | 1.2388 | |
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| 0.9031 | 15.02 | 11175 | 1.8899 | 0.1554 | 0.6312 | 0.5473 | 1.3054 | |
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| 0.7614 | 18.02 | 13410 | 1.5491 | 0.1522 | 0.6307 | 0.5349 | 1.0200 | |
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| 0.6483 | 21.03 | 15645 | 1.8357 | 0.1481 | 0.6304 | 0.5215 | 1.2852 | |
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| 0.5561 | 24.03 | 17880 | 2.0576 | 0.1468 | 0.6263 | 0.5191 | 1.4774 | |
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| 0.5108 | 27.04 | 20115 | 1.8949 | 0.1452 | 0.6351 | 0.5090 | 1.3489 | |
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| 0.4778 | 30.04 | 22350 | 1.7509 | 0.1453 | 0.6324 | 0.5111 | 1.2263 | |
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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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