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--- |
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library_name: transformers |
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license: mit |
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base_model: facebook/w2v-bert-2.0 |
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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: w2v-bert-2.0-CV_Fleurs-lg-5hrs-v5 |
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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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# w2v-bert-2.0-CV_Fleurs-lg-5hrs-v5 |
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4806 |
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- Wer: 0.4843 |
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- Cer: 0.1060 |
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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: 4 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 80 |
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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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| 2.5225 | 1.0 | 515 | 0.4996 | 0.5506 | 0.1117 | |
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| 0.4435 | 2.0 | 1030 | 0.4619 | 0.4623 | 0.0969 | |
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| 0.3765 | 3.0 | 1545 | 0.4473 | 0.5063 | 0.1061 | |
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| 0.3573 | 4.0 | 2060 | 0.4596 | 0.4672 | 0.0962 | |
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| 0.3421 | 5.0 | 2575 | 0.4621 | 0.5073 | 0.1093 | |
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| 0.3235 | 6.0 | 3090 | 0.4548 | 0.5074 | 0.1057 | |
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| 0.3263 | 7.0 | 3605 | 0.4454 | 0.4664 | 0.1011 | |
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| 0.3125 | 8.0 | 4120 | 0.5261 | 0.5385 | 0.1251 | |
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| 0.2963 | 9.0 | 4635 | 0.4753 | 0.4890 | 0.1108 | |
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| 0.2527 | 10.0 | 5150 | 0.4803 | 0.4869 | 0.1085 | |
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| 0.2328 | 11.0 | 5665 | 0.4830 | 0.4710 | 0.1008 | |
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| 0.2077 | 12.0 | 6180 | 0.4806 | 0.4843 | 0.1060 | |
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### Framework versions |
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- Transformers 4.46.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.1 |
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