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--- |
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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_528_10 |
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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_528_10 |
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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: 0.7757 |
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- Wer: 0.2425 |
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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: 0.0001 |
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- train_batch_size: 2 |
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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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- num_epochs: 8 |
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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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| 1.1878 | 0.3378 | 100 | 0.9689 | 0.3245 | |
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| 1.2219 | 0.6757 | 200 | 0.8869 | 0.2887 | |
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| 1.4146 | 1.0135 | 300 | 0.7800 | 0.2827 | |
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| 0.9472 | 1.3514 | 400 | 0.7899 | 0.2829 | |
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| 0.9176 | 1.6892 | 500 | 0.8345 | 0.2773 | |
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| 1.0975 | 2.0270 | 600 | 0.8103 | 0.2704 | |
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| 1.0267 | 2.3649 | 700 | 0.8043 | 0.2661 | |
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| 0.9401 | 2.7027 | 800 | 0.8001 | 0.2648 | |
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| 0.9752 | 3.0405 | 900 | 0.8112 | 0.2595 | |
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| 0.9301 | 3.3784 | 1000 | 0.8174 | 0.2593 | |
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| 0.7361 | 3.7162 | 1100 | 0.8497 | 0.2567 | |
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| 0.9846 | 4.0541 | 1200 | 0.8002 | 0.2513 | |
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| 0.9202 | 4.3919 | 1300 | 0.7937 | 0.2524 | |
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| 0.7069 | 4.7297 | 1400 | 0.8582 | 0.2448 | |
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| 1.0649 | 5.0676 | 1500 | 0.7993 | 0.2449 | |
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| 0.6096 | 5.4054 | 1600 | 0.8183 | 0.2442 | |
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| 0.6876 | 5.7432 | 1700 | 0.8041 | 0.2426 | |
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| 0.7614 | 6.0811 | 1800 | 0.8133 | 0.2454 | |
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| 0.572 | 6.4189 | 1900 | 0.7747 | 0.2441 | |
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| 0.5909 | 6.7568 | 2000 | 0.7610 | 0.2447 | |
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| 0.562 | 7.0946 | 2100 | 0.7784 | 0.2450 | |
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| 0.5979 | 7.4324 | 2200 | 0.7675 | 0.2427 | |
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| 0.541 | 7.7703 | 2300 | 0.7757 | 0.2425 | |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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