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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: 0.3699525493114998 |
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name: Wer |
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- type: bleu |
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value: 0.4072321954028345 |
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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: 0.2281 |
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- Wer: 0.3700 |
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- Cer: 0.0598 |
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- Bleu: 0.4072 |
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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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| 7.0089 | 1.5625 | 100 | 0.2991 | 0.4260 | 0.0693 | 0.3354 | |
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| 0.2087 | 3.125 | 200 | 0.2305 | 0.3968 | 0.0634 | 0.3678 | |
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| 0.1924 | 4.6875 | 300 | 0.2291 | 0.3879 | 0.0624 | 0.3799 | |
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| 0.1799 | 6.25 | 400 | 0.2290 | 0.3859 | 0.0629 | 0.3830 | |
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| 0.1698 | 7.8125 | 500 | 0.2224 | 0.3700 | 0.0600 | 0.4119 | |
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| 0.1587 | 9.375 | 600 | 0.2246 | 0.3672 | 0.0601 | 0.4129 | |
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| 0.1547 | 10.9375 | 700 | 0.2176 | 0.3855 | 0.0604 | 0.3820 | |
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| 0.1446 | 12.5 | 800 | 0.2273 | 0.3907 | 0.0619 | 0.3755 | |
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| 0.1404 | 14.0625 | 900 | 0.2239 | 0.3713 | 0.0605 | 0.4035 | |
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| 0.1333 | 15.625 | 1000 | 0.2261 | 0.3699 | 0.0602 | 0.4123 | |
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| 0.1251 | 17.1875 | 1100 | 0.2281 | 0.3700 | 0.0598 | 0.4072 | |
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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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