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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_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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# cmb-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: 0.1978 |
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- Per: 0.1287 |
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- Pcc: 0.6493 |
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- Ctc Loss: 0.4014 |
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- Mse Loss: 0.9499 |
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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: 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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| 11.3245 | 3.0 | 8928 | 4.4416 | 0.9956 | 0.6159 | 3.7640 | 0.8975 | |
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| 2.9636 | 6.0 | 17856 | 1.4930 | 0.1745 | 0.6638 | 0.6280 | 0.8352 | |
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| 1.0327 | 9.0 | 26784 | 1.3313 | 0.1461 | 0.6666 | 0.4797 | 0.8799 | |
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| 0.5448 | 12.0 | 35712 | 1.2880 | 0.1394 | 0.6530 | 0.4501 | 0.9425 | |
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| 0.1232 | 15.0 | 44640 | 1.0484 | 0.1354 | 0.6481 | 0.4289 | 0.8871 | |
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| -0.3248 | 18.0 | 53568 | 1.3777 | 0.1330 | 0.6373 | 0.4163 | 1.1622 | |
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| -0.7634 | 21.0 | 62496 | 1.0371 | 0.1312 | 0.6499 | 0.4094 | 1.0824 | |
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| -1.2089 | 24.0 | 71424 | 0.4166 | 0.1298 | 0.6454 | 0.4060 | 0.9053 | |
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| -1.613 | 27.0 | 80352 | 0.2751 | 0.1290 | 0.6473 | 0.4021 | 0.9426 | |
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| -1.8704 | 30.0 | 89280 | 0.1978 | 0.1287 | 0.6493 | 0.4014 | 0.9499 | |
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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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