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--- |
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base_model: ylacombe/w2v-bert-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_16_0 |
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metrics: |
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- wer |
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model-index: |
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- name: w2v-fine-tune-test-no-punct4 |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: common_voice_16_0 |
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type: common_voice_16_0 |
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config: tr |
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split: test |
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args: tr |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.436 |
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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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# w2v-fine-tune-test-no-punct4 |
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This model is a fine-tuned version of [ylacombe/w2v-bert-2.0](https://huggingface.co/ylacombe/w2v-bert-2.0) on the common_voice_16_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7511 |
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- Wer: 0.436 |
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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: 5e-05 |
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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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- 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: 20 |
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- num_epochs: 10 |
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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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| 4.367 | 1.54 | 20 | 3.3453 | 1.0 | |
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| 2.1265 | 3.08 | 40 | 1.7730 | 0.996 | |
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| 0.4755 | 4.62 | 60 | 0.8654 | 0.684 | |
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| 0.203 | 6.15 | 80 | 0.7436 | 0.56 | |
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| 0.1251 | 7.69 | 100 | 0.8143 | 0.548 | |
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| 0.0449 | 9.23 | 120 | 0.7511 | 0.436 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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