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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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metrics: |
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- wer |
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model-index: |
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- name: w2v2-base-pretrained_lr5e-5_at0.8_da0.05 |
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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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# w2v2-base-pretrained_lr5e-5_at0.8_da0.05 |
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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: 4.9499 |
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- Wer: 1.1098 |
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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: 5e-05 |
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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: 500 |
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- training_steps: 4000 |
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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 | Wer | |
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|:-------------:|:-------:|:----:|:---------------:|:------:| |
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| 32.094 | 83.33 | 250 | 3.6861 | 1.0 | |
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| 3.223 | 166.67 | 500 | 3.1064 | 1.0 | |
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| 3.0141 | 250.0 | 750 | 3.0722 | 1.0 | |
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| 2.6901 | 333.33 | 1000 | 2.8675 | 1.0 | |
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| 1.7283 | 416.67 | 1250 | 3.2044 | 1.0436 | |
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| 0.9791 | 500.0 | 1500 | 3.4905 | 1.0666 | |
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| 0.6506 | 583.33 | 1750 | 3.7132 | 1.0560 | |
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| 0.3895 | 666.67 | 2000 | 4.1587 | 1.0824 | |
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| 0.2399 | 750.0 | 2250 | 4.4319 | 1.1012 | |
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| 0.1794 | 833.33 | 2500 | 4.4773 | 1.0995 | |
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| 0.139 | 916.67 | 2750 | 4.6309 | 1.0871 | |
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| 0.1026 | 1000.0 | 3000 | 4.6925 | 1.0628 | |
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| 0.0807 | 1083.33 | 3250 | 4.8052 | 1.0824 | |
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| 0.0611 | 1166.67 | 3500 | 4.8086 | 1.0953 | |
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| 0.0539 | 1250.0 | 3750 | 4.8570 | 1.0995 | |
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| 0.0524 | 1333.33 | 4000 | 4.9499 | 1.1098 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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