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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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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: wav2vec2-xlsr-53-ft-btb-cv-other-cy |
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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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# wav2vec2-xlsr-53-ft-btb-cv-other-cy |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4934 |
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- Wer: 0.3776 |
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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: 64 |
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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: 800 |
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- training_steps: 8000 |
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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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| 5.1054 | 0.0755 | 500 | 2.8161 | 1.0 | |
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| 1.4196 | 0.1509 | 1000 | 1.1687 | 0.7941 | |
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| 1.0028 | 0.2264 | 1500 | 0.9890 | 0.6953 | |
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| 0.8942 | 0.3019 | 2000 | 0.8935 | 0.6195 | |
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| 0.8285 | 0.3774 | 2500 | 0.8221 | 0.6075 | |
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| 0.763 | 0.4528 | 3000 | 0.7165 | 0.5307 | |
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| 0.7203 | 0.5283 | 3500 | 0.6892 | 0.5054 | |
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| 0.7051 | 0.6038 | 4000 | 0.6848 | 0.5070 | |
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| 0.6568 | 0.6792 | 4500 | 0.6342 | 0.4926 | |
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| 0.6315 | 0.7547 | 5000 | 0.5956 | 0.4494 | |
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| 0.6171 | 0.8302 | 5500 | 0.5533 | 0.4305 | |
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| 0.5717 | 0.9057 | 6000 | 0.5360 | 0.4212 | |
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| 0.5699 | 0.9811 | 6500 | 0.5184 | 0.4040 | |
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| 0.4905 | 1.0566 | 7000 | 0.5081 | 0.3967 | |
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| 0.4706 | 1.1321 | 7500 | 0.4991 | 0.3825 | |
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| 0.4614 | 1.2075 | 8000 | 0.4934 | 0.3776 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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