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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_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_at0.8_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: 1.6691 |
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- Wer: 0.1858 |
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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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| 14.0341 | 5.43 | 250 | 3.5667 | 1.0 | |
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| 3.138 | 10.87 | 500 | 3.1976 | 1.0 | |
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| 3.0471 | 16.3 | 750 | 3.0452 | 1.0 | |
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| 1.3116 | 21.74 | 1000 | 1.0225 | 0.3358 | |
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| 0.1806 | 27.17 | 1250 | 1.2151 | 0.2533 | |
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| 0.1065 | 32.61 | 1500 | 1.2673 | 0.2384 | |
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| 0.0707 | 38.04 | 1750 | 1.4184 | 0.1888 | |
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| 0.0547 | 43.48 | 2000 | 1.6087 | 0.1901 | |
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| 0.0471 | 48.91 | 2250 | 1.4537 | 0.1880 | |
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| 0.0381 | 54.35 | 2500 | 1.6858 | 0.1845 | |
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| 0.0307 | 59.78 | 2750 | 1.5607 | 0.1961 | |
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| 0.0269 | 65.22 | 3000 | 1.6716 | 0.1862 | |
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| 0.024 | 70.65 | 3250 | 1.5554 | 0.1884 | |
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| 0.0199 | 76.09 | 3500 | 1.7169 | 0.1850 | |
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| 0.0187 | 81.52 | 3750 | 1.6661 | 0.1858 | |
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| 0.0176 | 86.96 | 4000 | 1.6691 | 0.1858 | |
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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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