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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base-960h |
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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: wtimit-base-960h-normal30percent-all |
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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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# wtimit-base-960h-normal30percent-all |
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This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8097 |
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- Wer: 0.3692 |
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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: 8 |
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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: 1000 |
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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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| 0.32 | 1.3889 | 1000 | 0.3506 | 0.2804 | |
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| 0.2342 | 2.7778 | 2000 | 0.4413 | 0.2977 | |
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| 0.183 | 4.1667 | 3000 | 0.4847 | 0.3134 | |
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| 0.1389 | 5.5556 | 4000 | 0.5576 | 0.3291 | |
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| 0.1156 | 6.9444 | 5000 | 0.6021 | 0.3405 | |
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| 0.1003 | 8.3333 | 6000 | 0.6778 | 0.3632 | |
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| 0.0921 | 9.7222 | 7000 | 0.6309 | 0.3549 | |
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| 0.0771 | 11.1111 | 8000 | 0.7765 | 0.3823 | |
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| 0.0674 | 12.5 | 9000 | 0.7512 | 0.3722 | |
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| 0.0629 | 13.8889 | 10000 | 0.6964 | 0.3764 | |
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| 0.0575 | 15.2778 | 11000 | 0.8090 | 0.3812 | |
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| 0.0531 | 16.6667 | 12000 | 0.8377 | 0.3919 | |
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| 0.044 | 18.0556 | 13000 | 0.8246 | 0.3881 | |
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| 0.0427 | 19.4444 | 14000 | 0.8331 | 0.3826 | |
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| 0.0415 | 20.8333 | 15000 | 0.8166 | 0.3800 | |
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| 0.0356 | 22.2222 | 16000 | 0.8550 | 0.3916 | |
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| 0.0359 | 23.6111 | 17000 | 0.7968 | 0.3843 | |
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| 0.0311 | 25.0 | 18000 | 0.8020 | 0.3788 | |
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| 0.0251 | 26.3889 | 19000 | 0.8026 | 0.3684 | |
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| 0.0264 | 27.7778 | 20000 | 0.7937 | 0.3743 | |
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| 0.0248 | 29.1667 | 21000 | 0.8097 | 0.3692 | |
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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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