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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: wav2vec2-19 |
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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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# wav2vec2-19 |
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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: 0.6305 |
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- Wer: 0.4499 |
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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: 0.0003 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 800 |
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- num_epochs: 60 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 3.4816 | 2.74 | 400 | 1.0717 | 0.8927 | |
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| 0.751 | 5.48 | 800 | 0.7155 | 0.7533 | |
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| 0.517 | 8.22 | 1200 | 0.7039 | 0.6675 | |
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| 0.3988 | 10.96 | 1600 | 0.5935 | 0.6149 | |
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| 0.3179 | 13.7 | 2000 | 0.6477 | 0.5999 | |
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| 0.2755 | 16.44 | 2400 | 0.5549 | 0.5798 | |
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| 0.2343 | 19.18 | 2800 | 0.6626 | 0.5798 | |
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| 0.2103 | 21.92 | 3200 | 0.6488 | 0.5674 | |
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| 0.1877 | 24.66 | 3600 | 0.5874 | 0.5339 | |
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| 0.1719 | 27.4 | 4000 | 0.6354 | 0.5389 | |
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| 0.1603 | 30.14 | 4400 | 0.6612 | 0.5210 | |
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| 0.1401 | 32.88 | 4800 | 0.6676 | 0.5131 | |
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| 0.1286 | 35.62 | 5200 | 0.6366 | 0.5075 | |
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| 0.1159 | 38.36 | 5600 | 0.6064 | 0.4977 | |
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| 0.1084 | 41.1 | 6000 | 0.6530 | 0.4835 | |
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| 0.0974 | 43.84 | 6400 | 0.6118 | 0.4853 | |
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| 0.0879 | 46.58 | 6800 | 0.6316 | 0.4770 | |
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| 0.0815 | 49.32 | 7200 | 0.6125 | 0.4664 | |
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| 0.0708 | 52.05 | 7600 | 0.6449 | 0.4683 | |
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| 0.0651 | 54.79 | 8000 | 0.6068 | 0.4571 | |
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| 0.0555 | 57.53 | 8400 | 0.6305 | 0.4499 | |
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### Framework versions |
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- Transformers 4.19.2 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.2.2 |
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- Tokenizers 0.12.1 |
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