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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: working |
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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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# working |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2584 |
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- Wer: 0.6024 |
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- Cer: 0.0723 |
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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: 3e-05 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 4 |
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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: 2000 |
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- training_steps: 70000 |
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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 | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| |
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| 2.0401 | 1.49 | 1000 | 1.3913 | 0.9911 | 0.4127 | |
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| 1.2772 | 2.98 | 2000 | 0.4117 | 0.7644 | 0.1036 | |
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| 1.0861 | 4.46 | 3000 | 0.3281 | 0.6962 | 0.0868 | |
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| 1.0803 | 5.95 | 4000 | 0.2970 | 0.6645 | 0.0796 | |
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| 1.0256 | 7.44 | 5000 | 0.2986 | 0.6556 | 0.0820 | |
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| 0.9536 | 8.93 | 6000 | 0.2873 | 0.6418 | 0.0767 | |
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| 0.9154 | 10.42 | 7000 | 0.3896 | 0.6450 | 0.0812 | |
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| 0.9187 | 11.9 | 8000 | 0.2946 | 0.6239 | 0.0771 | |
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| 0.8693 | 13.39 | 9000 | 0.2655 | 0.6093 | 0.0746 | |
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| 0.8335 | 14.88 | 10000 | 0.2797 | 0.6052 | 0.0764 | |
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| 0.8461 | 16.37 | 11000 | 0.2879 | 0.6231 | 0.0766 | |
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| 0.8363 | 17.86 | 12000 | 0.2616 | 0.6052 | 0.0726 | |
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| 0.796 | 19.35 | 13000 | 0.2656 | 0.6109 | 0.0740 | |
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| 0.8136 | 20.83 | 14000 | 0.2773 | 0.6255 | 0.0747 | |
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| 0.7319 | 22.32 | 15000 | 0.2770 | 0.6214 | 0.0748 | |
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| 0.7428 | 23.81 | 16000 | 0.2697 | 0.6052 | 0.0746 | |
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| 0.7264 | 25.3 | 17000 | 0.2716 | 0.5971 | 0.0733 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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