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--- |
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base_model: facebook/mms-1b-all |
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datasets: |
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- common_voice_17_0 |
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library_name: transformers |
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license: cc-by-nc-4.0 |
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metrics: |
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- wer |
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- bleu |
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tags: |
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- generated_from_trainer |
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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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type: automatic-speech-recognition |
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name: 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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- type: wer |
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value: 0.41655589677774213 |
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name: Wer |
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- type: bleu |
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value: 0.3602695476100989 |
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name: Bleu |
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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: 0.3166 |
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- Wer: 0.4166 |
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- Cer: 0.0689 |
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- Bleu: 0.3603 |
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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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| 11.8671 | 3.125 | 50 | 3.8104 | 1.0011 | 0.9249 | 0.0 | |
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| 1.5965 | 6.25 | 100 | 0.2796 | 0.4122 | 0.0680 | 0.3517 | |
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| 0.2054 | 9.375 | 150 | 0.2320 | 0.3751 | 0.0620 | 0.4040 | |
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| 0.1702 | 12.5 | 200 | 0.2367 | 0.3794 | 0.0633 | 0.3939 | |
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| 0.1495 | 15.625 | 250 | 0.2527 | 0.4168 | 0.0680 | 0.3457 | |
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| 0.1457 | 18.75 | 300 | 0.2536 | 0.3973 | 0.0662 | 0.3723 | |
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| 0.1264 | 21.875 | 350 | 0.2765 | 0.4175 | 0.0693 | 0.3546 | |
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| 0.1092 | 25.0 | 400 | 0.2711 | 0.4032 | 0.0673 | 0.3701 | |
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| 0.0952 | 28.125 | 450 | 0.2828 | 0.4139 | 0.0691 | 0.3605 | |
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| 0.0919 | 31.25 | 500 | 0.2972 | 0.4283 | 0.0721 | 0.3355 | |
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| 0.0909 | 34.375 | 550 | 0.2971 | 0.4155 | 0.0686 | 0.3567 | |
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| 0.0744 | 37.5 | 600 | 0.3086 | 0.4241 | 0.0705 | 0.3461 | |
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| 0.069 | 40.625 | 650 | 0.3166 | 0.4166 | 0.0689 | 0.3603 | |
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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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