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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: 0.4958060228262364 |
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name: Wer |
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- type: bleu |
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value: 0.2629057639184852 |
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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: 0.5099 |
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- Wer: 0.4958 |
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- Cer: 0.0885 |
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- Bleu: 0.2629 |
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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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| 11.4061 | 50.0 | 50 | 4.6415 | 1.0007 | 0.9640 | 0.0 | |
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| 1.789 | 100.0 | 100 | 0.3026 | 0.4457 | 0.0734 | 0.3064 | |
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| 0.08 | 150.0 | 150 | 0.3223 | 0.4304 | 0.0711 | 0.3275 | |
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| 0.0473 | 200.0 | 200 | 0.3547 | 0.4426 | 0.0742 | 0.3156 | |
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| 0.0364 | 250.0 | 250 | 0.3786 | 0.4556 | 0.0761 | 0.2972 | |
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| 0.0298 | 300.0 | 300 | 0.4070 | 0.4629 | 0.0800 | 0.2875 | |
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| 0.0279 | 350.0 | 350 | 0.4190 | 0.4688 | 0.0799 | 0.2864 | |
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| 0.0253 | 400.0 | 400 | 0.4353 | 0.4755 | 0.0818 | 0.2757 | |
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| 0.0198 | 450.0 | 450 | 0.4808 | 0.5066 | 0.0887 | 0.2432 | |
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| 0.0216 | 500.0 | 500 | 0.4699 | 0.4780 | 0.0815 | 0.2777 | |
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| 0.0194 | 550.0 | 550 | 0.4745 | 0.4895 | 0.0877 | 0.2643 | |
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| 0.0201 | 600.0 | 600 | 0.5035 | 0.4971 | 0.0881 | 0.2647 | |
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| 0.0153 | 650.0 | 650 | 0.5099 | 0.4958 | 0.0885 | 0.2629 | |
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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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