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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: openai/whisper-large-v2 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- generator |
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model-index: |
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- name: whisper-large-v2-multilingual |
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results: [] |
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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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# whisper-large-v2-multilingual |
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3502 |
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- Wer Eng: 0.01 |
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- Wer Lug: 0.106 |
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- Wer Ach: 0.241 |
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- Wer Lgg: 0.361 |
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- Wer Teo: 0.327 |
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- Wer Nyn: 0.387 |
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- Wer Mean: 0.239 |
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- Cer Eng: 0.004 |
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- Cer Lug: 0.029 |
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- Cer Ach: 0.064 |
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- Cer Lgg: 0.118 |
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- Cer Teo: 0.145 |
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- Cer Nyn: 0.125 |
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- Cer Mean: 0.081 |
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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: 1e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 256 |
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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_steps: 50 |
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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 Eng | Wer Lug | Wer Ach | Wer Lgg | Wer Teo | Wer Nyn | Wer Mean | Cer Eng | Cer Lug | Cer Ach | Cer Lgg | Cer Teo | Cer Nyn | Cer Mean | |
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|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|:--------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|:--------:| |
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| 1.0754 | 0.1 | 200 | 0.6042 | 0.031 | 0.267 | 0.428 | 0.481 | 0.615 | 0.712 | 0.422 | 0.017 | 0.053 | 0.121 | 0.147 | 0.242 | 0.201 | 0.13 | |
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| 0.5269 | 1.0001 | 400 | 0.4731 | 0.018 | 0.176 | 0.34 | 0.422 | 0.45 | 0.531 | 0.323 | 0.008 | 0.04 | 0.093 | 0.126 | 0.174 | 0.156 | 0.099 | |
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| 0.4203 | 1.1001 | 600 | 0.4230 | 0.018 | 0.199 | 0.319 | 0.416 | 0.418 | 0.482 | 0.309 | 0.007 | 0.06 | 0.094 | 0.122 | 0.163 | 0.146 | 0.099 | |
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| 0.3851 | 2.0002 | 800 | 0.3871 | 0.014 | 0.116 | 0.271 | 0.374 | 0.443 | 0.454 | 0.279 | 0.006 | 0.03 | 0.073 | 0.11 | 0.19 | 0.137 | 0.091 | |
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| 0.3241 | 2.1002 | 1000 | 0.3716 | 0.015 | 0.12 | 0.271 | 0.392 | 0.397 | 0.416 | 0.269 | 0.006 | 0.03 | 0.077 | 0.133 | 0.166 | 0.127 | 0.09 | |
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| 0.3161 | 3.0004 | 1200 | 0.3584 | 0.021 | 0.121 | 0.269 | 0.429 | 0.36 | 0.38 | 0.263 | 0.008 | 0.032 | 0.071 | 0.154 | 0.16 | 0.121 | 0.091 | |
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| 0.2764 | 3.1004 | 1400 | 0.3546 | 0.012 | 0.116 | 0.254 | 0.376 | 0.348 | 0.403 | 0.251 | 0.004 | 0.03 | 0.073 | 0.123 | 0.155 | 0.125 | 0.085 | |
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| 0.2692 | 4.0005 | 1600 | 0.3487 | 0.011 | 0.107 | 0.248 | 0.352 | 0.336 | 0.377 | 0.238 | 0.004 | 0.029 | 0.067 | 0.102 | 0.15 | 0.123 | 0.079 | |
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| 0.2427 | 4.1005 | 1800 | 0.3535 | 0.01 | 0.113 | 0.24 | 0.384 | 0.329 | 0.387 | 0.244 | 0.004 | 0.03 | 0.066 | 0.122 | 0.145 | 0.125 | 0.082 | |
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| 0.2413 | 5.0006 | 2000 | 0.3502 | 0.01 | 0.106 | 0.241 | 0.361 | 0.327 | 0.387 | 0.239 | 0.004 | 0.029 | 0.064 | 0.118 | 0.145 | 0.125 | 0.081 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.2.1 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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