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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_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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# pic-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: 1.4215 |
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- Per: 0.1497 |
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- Pcc: 0.6339 |
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- Ctc Loss: 0.5259 |
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- Mse Loss: 0.8821 |
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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: 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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| 17.0464 | 3.0 | 2247 | 5.0097 | 0.9979 | 0.6184 | 3.7876 | 1.2860 | |
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| 4.3019 | 6.0 | 4494 | 4.2229 | 0.9979 | 0.7055 | 3.7328 | 0.6675 | |
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| 3.9383 | 9.0 | 6741 | 4.1717 | 0.9979 | 0.7012 | 3.7059 | 0.7331 | |
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| 3.3316 | 12.0 | 8988 | 2.9515 | 0.6216 | 0.6761 | 2.3269 | 0.7956 | |
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| 1.5694 | 15.0 | 11235 | 1.8634 | 0.2235 | 0.6674 | 0.8822 | 0.9706 | |
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| 0.8929 | 18.0 | 13482 | 1.5733 | 0.1742 | 0.6392 | 0.6657 | 0.8867 | |
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| 0.6847 | 21.0 | 15729 | 1.6522 | 0.1613 | 0.6497 | 0.5817 | 1.0250 | |
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| 0.5739 | 24.0 | 17976 | 1.4394 | 0.1534 | 0.6165 | 0.5482 | 0.8750 | |
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| 0.5063 | 27.0 | 20223 | 1.4105 | 0.1510 | 0.6296 | 0.5322 | 0.8668 | |
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| 0.4701 | 30.0 | 22470 | 1.4215 | 0.1497 | 0.6339 | 0.5259 | 0.8821 | |
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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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