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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_531 |
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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_531 |
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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: 0.7843 |
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- Wer: 0.2445 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:------:|:----:|:---------------:|:------:| |
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| 1.1649 | 0.3378 | 100 | 0.9661 | 0.3229 | |
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| 1.2208 | 0.6757 | 200 | 0.8651 | 0.2918 | |
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| 1.412 | 1.0135 | 300 | 0.7681 | 0.2915 | |
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| 0.9419 | 1.3514 | 400 | 0.7712 | 0.2818 | |
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| 0.9161 | 1.6892 | 500 | 0.8276 | 0.2776 | |
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| 1.0943 | 2.0270 | 600 | 0.8074 | 0.2706 | |
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| 1.0036 | 2.3649 | 700 | 0.7917 | 0.2691 | |
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| 0.9262 | 2.7027 | 800 | 0.7897 | 0.2644 | |
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| 0.9841 | 3.0405 | 900 | 0.8006 | 0.2590 | |
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| 0.9327 | 3.3784 | 1000 | 0.8068 | 0.2630 | |
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| 0.7249 | 3.7162 | 1100 | 0.8546 | 0.2533 | |
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| 0.9704 | 4.0541 | 1200 | 0.8350 | 0.2533 | |
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| 0.8985 | 4.3919 | 1300 | 0.8414 | 0.2478 | |
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| 0.6858 | 4.7297 | 1400 | 0.8533 | 0.2469 | |
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| 1.0581 | 5.0676 | 1500 | 0.8200 | 0.2459 | |
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| 0.5899 | 5.4054 | 1600 | 0.8378 | 0.2459 | |
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| 0.6891 | 5.7432 | 1700 | 0.8094 | 0.2478 | |
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| 0.7276 | 6.0811 | 1800 | 0.8326 | 0.2438 | |
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| 0.5738 | 6.4189 | 1900 | 0.7844 | 0.2456 | |
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| 0.5837 | 6.7568 | 2000 | 0.7773 | 0.2473 | |
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| 0.5476 | 7.0946 | 2100 | 0.7725 | 0.2488 | |
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| 0.6004 | 7.4324 | 2200 | 0.7693 | 0.2471 | |
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| 0.5391 | 7.7703 | 2300 | 0.7843 | 0.2445 | |
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### Framework versions |
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- Transformers 4.41.1 |
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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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