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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: facebook/hubert-large-ls960-ft |
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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-large-timit-upsample-decoder |
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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-large-timit-upsample-decoder |
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This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co/facebook/hubert-large-ls960-ft) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4975 |
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- Wer: 0.9749 |
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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: 0.0003 |
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- train_batch_size: 8 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 40 |
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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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| 83.048 | 2.4752 | 500 | 48.3229 | 0.9459 | |
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| 2.1777 | 4.9505 | 1000 | 3.3841 | 0.9775 | |
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| 2.5735 | 7.4257 | 1500 | 2.1042 | 0.9698 | |
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| 5.3683 | 9.9010 | 2000 | 1.5244 | 0.9699 | |
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| 1.906 | 12.3762 | 2500 | 1.3064 | 0.9128 | |
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| 1.9468 | 14.8515 | 3000 | 1.3597 | 0.9174 | |
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| 1.6598 | 17.3267 | 3500 | 1.1801 | 0.9093 | |
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| 1.2808 | 19.8020 | 4000 | 1.6481 | 0.9181 | |
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| 2.0953 | 22.2772 | 4500 | 3.1021 | 0.9602 | |
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| 0.5282 | 24.7525 | 5000 | 0.5278 | 0.9755 | |
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| 7.1607 | 27.2277 | 5500 | 0.9557 | 0.9823 | |
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| 4.1975 | 29.7030 | 6000 | 13.0365 | 0.9301 | |
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| 0.5248 | 32.1782 | 6500 | 0.5075 | 0.9840 | |
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| 0.5065 | 34.6535 | 7000 | 0.5001 | 0.9834 | |
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| 0.4997 | 37.1287 | 7500 | 0.5032 | 0.9793 | |
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| 0.5072 | 39.6040 | 8000 | 0.4975 | 0.9749 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.2.1 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
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