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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: 0.4582664894348444 |
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name: Wer |
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- type: bleu |
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value: 0.3001349308741465 |
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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: 0.4355 |
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- Wer: 0.4583 |
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- Cer: 0.0787 |
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- Bleu: 0.3001 |
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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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| 12.8763 | 25.0 | 50 | 4.9690 | 1.0000 | 0.9319 | 0.0 | |
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| 2.2038 | 50.0 | 100 | 0.3040 | 0.4239 | 0.0696 | 0.3337 | |
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| 0.1153 | 75.0 | 150 | 0.2911 | 0.4134 | 0.0685 | 0.3474 | |
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| 0.0557 | 100.0 | 200 | 0.3344 | 0.4333 | 0.0718 | 0.3271 | |
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| 0.0448 | 125.0 | 250 | 0.3486 | 0.4403 | 0.0743 | 0.3213 | |
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| 0.0382 | 150.0 | 300 | 0.3938 | 0.4499 | 0.0762 | 0.3102 | |
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| 0.0364 | 175.0 | 350 | 0.3927 | 0.4525 | 0.0778 | 0.3045 | |
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| 0.0286 | 200.0 | 400 | 0.3883 | 0.4417 | 0.0744 | 0.3173 | |
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| 0.0293 | 225.0 | 450 | 0.4235 | 0.4656 | 0.0794 | 0.2913 | |
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| 0.0296 | 250.0 | 500 | 0.4432 | 0.4710 | 0.0817 | 0.2771 | |
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| 0.0302 | 275.0 | 550 | 0.4266 | 0.4524 | 0.0765 | 0.3016 | |
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| 0.0252 | 300.0 | 600 | 0.4376 | 0.4717 | 0.0815 | 0.2793 | |
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| 0.0216 | 325.0 | 650 | 0.4355 | 0.4583 | 0.0787 | 0.3001 | |
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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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