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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_at0.3_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_at0.3_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: 1.4352 |
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- Wer: 0.1704 |
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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: 1000 |
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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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| 19.6725 | 3.97 | 250 | 4.9409 | 1.0 | |
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| 3.5043 | 7.94 | 500 | 3.2414 | 1.0 | |
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| 3.1162 | 11.9 | 750 | 3.1351 | 1.0 | |
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| 2.2138 | 15.87 | 1000 | 0.9146 | 0.9184 | |
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| 0.5308 | 19.84 | 1250 | 0.6292 | 0.4357 | |
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| 0.2762 | 23.81 | 1500 | 0.8713 | 0.2384 | |
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| 0.1894 | 27.78 | 1750 | 0.9537 | 0.1905 | |
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| 0.1339 | 31.75 | 2000 | 1.2355 | 0.1824 | |
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| 0.1002 | 35.71 | 2250 | 1.2193 | 0.1739 | |
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| 0.0858 | 39.68 | 2500 | 1.1557 | 0.1709 | |
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| 0.0711 | 43.65 | 2750 | 1.3591 | 0.1692 | |
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| 0.0589 | 47.62 | 3000 | 1.3372 | 0.1683 | |
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| 0.0525 | 51.59 | 3250 | 1.4133 | 0.1683 | |
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| 0.0464 | 55.56 | 3500 | 1.4969 | 0.1679 | |
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| 0.0436 | 59.52 | 3750 | 1.4262 | 0.1674 | |
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| 0.0401 | 63.49 | 4000 | 1.4352 | 0.1704 | |
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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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