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--- |
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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: hubert-base-libri-pruning-v2-testing4 |
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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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# hubert-base-libri-pruning-v2-testing4 |
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This model was trained from scratch on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: -7567.2393 |
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- Wer: 0.4152 |
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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: 0.00015 |
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- train_batch_size: 64 |
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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: 3000 |
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- num_epochs: 30 |
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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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| -14.3764 | 1.12 | 500 | -47.0110 | 0.5199 | |
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| -106.5551 | 2.24 | 1000 | -189.6375 | 0.4788 | |
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| -290.9837 | 3.36 | 1500 | -427.6701 | 0.4637 | |
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| -566.8718 | 4.48 | 2000 | -760.7963 | 0.4523 | |
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| -932.8283 | 5.61 | 2500 | -1188.8673 | 0.4457 | |
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| -1393.9495 | 6.73 | 3000 | -1711.7064 | 0.4362 | |
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| -1926.4679 | 7.85 | 3500 | -2267.1279 | 0.4336 | |
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| -2446.4408 | 8.97 | 4000 | -2795.6897 | 0.4307 | |
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| -2944.8128 | 10.09 | 4500 | -3294.3000 | 0.4279 | |
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| -3416.905 | 11.21 | 5000 | -3766.8943 | 0.4254 | |
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| -3865.4817 | 12.33 | 5500 | -4211.6885 | 0.4219 | |
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| -4285.8215 | 13.45 | 6000 | -4628.7329 | 0.4223 | |
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| -4660.695 | 14.57 | 6500 | -5017.9912 | 0.4184 | |
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| -5032.002 | 15.7 | 7000 | -5379.4785 | 0.4213 | |
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| -5351.629 | 16.82 | 7500 | -5713.4419 | 0.4186 | |
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| -5659.1765 | 17.94 | 8000 | -6019.7510 | 0.4195 | |
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| -5957.58 | 19.06 | 8500 | -6296.5054 | 0.4189 | |
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| -6215.3305 | 20.18 | 9000 | -6547.0381 | 0.4165 | |
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| -6441.2955 | 21.3 | 9500 | -6770.7163 | 0.4172 | |
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| -6651.3045 | 22.42 | 10000 | -6966.9087 | 0.4160 | |
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| -6811.32 | 23.54 | 10500 | -7135.6860 | 0.4155 | |
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| -6964.2775 | 24.66 | 11000 | -7277.1060 | 0.4171 | |
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| -7115.7955 | 25.78 | 11500 | -7390.9673 | 0.4156 | |
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| -7187.0235 | 26.91 | 12000 | -7477.7656 | 0.4151 | |
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| -7259.9035 | 28.03 | 12500 | -7535.0112 | 0.4148 | |
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| -7302.289 | 29.15 | 13000 | -7567.2393 | 0.4152 | |
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### Framework versions |
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- Transformers 4.30.0.dev0 |
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- Pytorch 2.0.1 |
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- Datasets 2.12.1.dev0 |
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- Tokenizers 0.13.3 |
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