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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: libri-smallw2v2-no-copy-mse-alpha-0.75-T-1-take-5 |
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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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# libri-smallw2v2-no-copy-mse-alpha-0.75-T-1-take-5 |
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This model is a fine-tuned version of [rohitp1/libri-smallw2v2-no-copy-mse-alpha-0.75-T-1-take-3](https://huggingface.co/rohitp1/libri-smallw2v2-no-copy-mse-alpha-0.75-T-1-take-3) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 30.3050 |
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- Wer: 0.2650 |
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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: 0.002 |
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- train_batch_size: 4 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 64 |
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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_ratio: 0.2 |
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- num_epochs: 100 |
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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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| 239.4865 | 1.12 | 400 | 31.0836 | 0.2908 | |
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| 210.2046 | 2.25 | 800 | 29.7831 | 0.2742 | |
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| 195.0478 | 3.37 | 1200 | 28.8794 | 0.2636 | |
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| 188.8096 | 4.49 | 1600 | 28.7458 | 0.2600 | |
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| 183.6592 | 5.62 | 2000 | 29.1159 | 0.2573 | |
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| 181.5025 | 6.74 | 2400 | 29.0081 | 0.2564 | |
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| 181.9954 | 7.86 | 2800 | 28.7132 | 0.2588 | |
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| 181.8548 | 8.99 | 3200 | 29.3207 | 0.2630 | |
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| 186.2524 | 10.11 | 3600 | 29.9119 | 0.2593 | |
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| 188.3838 | 11.24 | 4000 | 30.2963 | 0.2627 | |
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| 192.2623 | 12.36 | 4400 | 30.3050 | 0.2650 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.12.1 |
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- Datasets 2.7.1 |
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- Tokenizers 0.11.0 |
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