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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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model-index: |
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- name: wav2vec2_ljspeech_with_stress |
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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_ljspeech_with_stress |
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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 the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0431 |
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- Cer: 0.0073 |
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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: 16 |
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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: 32 |
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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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 2.9043 | 1.53 | 500 | 3.0446 | 1.0 | |
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| 1.1195 | 3.05 | 1000 | 0.1302 | 0.0233 | |
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| 0.1656 | 4.58 | 1500 | 0.0728 | 0.0149 | |
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| 0.1136 | 6.11 | 2000 | 0.0581 | 0.0122 | |
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| 0.0852 | 7.63 | 2500 | 0.0508 | 0.0102 | |
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| 0.0746 | 9.16 | 3000 | 0.0472 | 0.0093 | |
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| 0.0646 | 10.69 | 3500 | 0.0443 | 0.0084 | |
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| 0.0588 | 12.21 | 4000 | 0.0442 | 0.0081 | |
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| 0.0513 | 13.74 | 4500 | 0.0437 | 0.0077 | |
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| 0.046 | 15.27 | 5000 | 0.0435 | 0.0075 | |
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| 0.0446 | 16.79 | 5500 | 0.0430 | 0.0075 | |
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| 0.0429 | 18.32 | 6000 | 0.0433 | 0.0074 | |
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| 0.0412 | 19.85 | 6500 | 0.0431 | 0.0072 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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