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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_at0.6_da1 |
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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_at0.6_da1 |
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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: 1.4542 |
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- Wer: 0.1867 |
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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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| 14.9488 | 4.24 | 250 | 3.6144 | 1.0 | |
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| 3.1468 | 8.47 | 500 | 3.2251 | 1.0 | |
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| 2.5166 | 12.71 | 750 | 1.3839 | 0.9603 | |
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| 0.4698 | 16.95 | 1000 | 0.6829 | 0.2909 | |
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| 0.2122 | 21.19 | 1250 | 0.9930 | 0.2217 | |
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| 0.1236 | 25.42 | 1500 | 1.1644 | 0.2140 | |
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| 0.0898 | 29.66 | 1750 | 1.0494 | 0.2076 | |
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| 0.0664 | 33.9 | 2000 | 1.1845 | 0.2093 | |
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| 0.0521 | 38.14 | 2250 | 1.2057 | 0.2089 | |
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| 0.0417 | 42.37 | 2500 | 1.3375 | 0.1914 | |
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| 0.0359 | 46.61 | 2750 | 1.5455 | 0.1880 | |
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| 0.0315 | 50.85 | 3000 | 1.3454 | 0.1884 | |
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| 0.0267 | 55.08 | 3250 | 1.2789 | 0.1944 | |
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| 0.0239 | 59.32 | 3500 | 1.3917 | 0.1909 | |
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| 0.0223 | 63.56 | 3750 | 1.4291 | 0.1897 | |
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| 0.0202 | 67.8 | 4000 | 1.4542 | 0.1867 | |
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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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