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README.md
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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-TEST13
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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-TEST13
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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: -0.0766
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- Wer: 0.1385
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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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| 0.1633 | 1.12 | 500 | 0.1342 | 0.1128 |
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| 0.1467 | 2.24 | 1000 | 0.1452 | 0.1173 |
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| 0.137 | 3.36 | 1500 | 0.1459 | 0.1174 |
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| 0.1382 | 4.48 | 2000 | 0.1362 | 0.1172 |
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| 0.1123 | 5.61 | 2500 | 0.1036 | 0.1172 |
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| 0.0701 | 6.73 | 3000 | 0.0685 | 0.1135 |
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| 0.0496 | 7.85 | 3500 | 0.0547 | 0.1172 |
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| 0.0329 | 8.97 | 4000 | 0.0333 | 0.1172 |
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| 0.0105 | 10.09 | 4500 | 0.0148 | 0.1175 |
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| -0.0203 | 11.21 | 5000 | -0.0041 | 0.1171 |
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| -0.0334 | 12.33 | 5500 | -0.0208 | 0.1170 |
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| -0.0549 | 13.45 | 6000 | -0.0392 | 0.1170 |
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| -0.0688 | 14.57 | 6500 | -0.0535 | 0.1170 |
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| -0.0751 | 15.7 | 7000 | -0.0670 | 0.1170 |
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| -0.09 | 16.82 | 7500 | -0.0816 | 0.1169 |
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| -0.1026 | 17.94 | 8000 | -0.0919 | 0.1177 |
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| -0.1161 | 19.06 | 8500 | -0.1012 | 0.1176 |
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| -0.1192 | 20.18 | 9000 | -0.1104 | 0.1176 |
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| -0.1303 | 21.3 | 9500 | -0.0413 | 0.1386 |
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| -0.1426 | 22.42 | 10000 | -0.0510 | 0.1389 |
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| -0.141 | 23.54 | 10500 | -0.0576 | 0.1385 |
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| -0.1489 | 24.66 | 11000 | -0.0637 | 0.1386 |
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| -0.1492 | 25.78 | 11500 | -0.0681 | 0.1386 |
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| -0.1619 | 26.91 | 12000 | -0.0728 | 0.1383 |
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| -0.1567 | 28.03 | 12500 | -0.0755 | 0.1384 |
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| -0.1627 | 29.15 | 13000 | -0.0766 | 0.1385 |
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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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