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--- |
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library_name: transformers |
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license: cc-by-nc-4.0 |
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base_model: facebook/mms-1b-all |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_17_0 |
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metrics: |
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- wer |
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- bleu |
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model-index: |
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- name: wav2vec2-mms-1b-CV17.0-training_set_variations |
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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_17_0 |
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type: common_voice_17_0 |
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config: ta |
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split: validation |
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args: ta |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.5038262932638631 |
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- name: Bleu |
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type: bleu |
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value: 0.25352723931305554 |
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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-mms-1b-CV17.0-training_set_variations |
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This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5467 |
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- Wer: 0.5038 |
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- Cer: 0.0871 |
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- Bleu: 0.2535 |
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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: 0.001 |
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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_ratio: 0.15 |
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- training_steps: 2000 |
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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 | Bleu | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:| |
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| 7.5761 | 100.0 | 100 | 0.3128 | 0.4455 | 0.0729 | 0.3095 | |
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| 0.067 | 200.0 | 200 | 0.3441 | 0.4234 | 0.0706 | 0.3389 | |
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| 0.0307 | 300.0 | 300 | 0.3906 | 0.4489 | 0.0749 | 0.3100 | |
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| 0.0251 | 400.0 | 400 | 0.4461 | 0.4745 | 0.0802 | 0.2744 | |
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| 0.0205 | 500.0 | 500 | 0.4579 | 0.4834 | 0.0820 | 0.2714 | |
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| 0.0166 | 600.0 | 600 | 0.4550 | 0.4742 | 0.0823 | 0.2837 | |
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| 0.0123 | 700.0 | 700 | 0.5467 | 0.5038 | 0.0871 | 0.2535 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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