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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: 1.0759957831049183 |
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- name: Bleu |
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type: bleu |
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value: 0.0 |
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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: 6.3100 |
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- Wer: 1.0760 |
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- Cer: 0.7242 |
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- Bleu: 0.0 |
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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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| 13.5071 | 6.25 | 50 | 7.0048 | 1.0001 | 0.9823 | 0.0 | |
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| 5.6893 | 12.5 | 100 | 5.2167 | 1.0000 | 0.9089 | 0.0 | |
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| 4.3569 | 18.75 | 150 | 4.3516 | 1.0125 | 0.8661 | 0.0 | |
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| 3.5211 | 25.0 | 200 | 3.5506 | 1.0269 | 0.8318 | 0.0 | |
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| 3.2359 | 31.25 | 250 | 3.4822 | 1.0039 | 0.8458 | 0.0 | |
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| 3.1004 | 37.5 | 300 | 3.5209 | 1.0086 | 0.8185 | 0.0 | |
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| 2.9953 | 43.75 | 350 | 3.5498 | 1.0121 | 0.8104 | 0.0 | |
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| 2.779 | 50.0 | 400 | 3.6218 | 1.0170 | 0.7777 | 0.0 | |
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| 2.6019 | 56.25 | 450 | 4.0907 | 1.0134 | 0.7504 | 0.0 | |
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| 2.4589 | 62.5 | 500 | 3.8633 | 1.0287 | 0.7476 | 0.0 | |
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| 2.2318 | 68.75 | 550 | 3.7976 | 1.0367 | 0.7239 | 0.0 | |
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| 2.0073 | 75.0 | 600 | 4.0050 | 1.0234 | 0.7288 | 0.0 | |
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| 1.7416 | 81.25 | 650 | 4.2022 | 1.0126 | 0.7231 | 0.0 | |
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| 1.5467 | 87.5 | 700 | 4.4087 | 1.0469 | 0.7197 | 0.0 | |
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| 1.3716 | 93.75 | 750 | 4.5391 | 1.0471 | 0.7185 | 0.0 | |
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| 1.2237 | 100.0 | 800 | 4.8405 | 1.0398 | 0.7152 | 0.0 | |
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| 1.1216 | 106.25 | 850 | 5.0209 | 1.0421 | 0.7160 | 0.0 | |
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| 1.0274 | 112.5 | 900 | 5.0349 | 1.0669 | 0.7160 | 0.0 | |
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| 0.9325 | 118.75 | 950 | 5.2384 | 1.0500 | 0.7198 | 0.0 | |
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| 0.8486 | 125.0 | 1000 | 5.3843 | 1.0614 | 0.7131 | 0.0 | |
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| 0.7996 | 131.25 | 1050 | 5.4558 | 1.0622 | 0.7181 | 0.0 | |
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| 0.7479 | 137.5 | 1100 | 5.6746 | 1.0622 | 0.7205 | 0.0 | |
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| 0.6972 | 143.75 | 1150 | 5.7069 | 1.1182 | 0.7218 | 0.0 | |
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| 0.6596 | 150.0 | 1200 | 5.7678 | 1.0883 | 0.7221 | 0.0 | |
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| 0.6213 | 156.25 | 1250 | 5.9645 | 1.0700 | 0.7191 | 0.0 | |
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| 0.5905 | 162.5 | 1300 | 6.0098 | 1.0970 | 0.7210 | 0.0 | |
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| 0.5532 | 168.75 | 1350 | 6.0379 | 1.0981 | 0.7235 | 0.0 | |
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| 0.5336 | 175.0 | 1400 | 6.2079 | 1.0564 | 0.7210 | 0.0 | |
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| 0.4955 | 181.25 | 1450 | 6.1618 | 1.0717 | 0.7225 | 0.0 | |
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| 0.4851 | 187.5 | 1500 | 6.3100 | 1.0760 | 0.7242 | 0.0 | |
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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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