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--- |
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base_model: openai/whisper-medium |
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datasets: |
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- generator |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: whisper-medium-sb-lug-eng-v2 |
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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-medium-sb-lug-eng-v2 |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1255 |
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- Wer Lug: 0.124 |
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- Wer Eng: 0.171 |
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- Wer Mean: 0.147 |
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- Cer Lug: 0.028 |
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- Cer Eng: 0.164 |
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- Cer Mean: 0.096 |
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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: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 500 |
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- training_steps: 5000 |
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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 Lug | Wer Eng | Wer Mean | Cer Lug | Cer Eng | Cer Mean | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:--------:|:-------:|:-------:|:--------:| |
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| 0.7222 | 0.1 | 500 | 0.2662 | 0.391 | 0.146 | 0.268 | 0.085 | 0.104 | 0.095 | |
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| 0.5452 | 0.2 | 1000 | 0.1894 | 0.223 | 0.058 | 0.141 | 0.05 | 0.034 | 0.042 | |
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| 0.4172 | 0.3 | 1500 | 0.1764 | 0.199 | 0.276 | 0.238 | 0.043 | 0.269 | 0.156 | |
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| 0.3949 | 0.4 | 2000 | 0.1583 | 0.177 | 0.035 | 0.106 | 0.039 | 0.017 | 0.028 | |
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| 0.3626 | 0.5 | 2500 | 0.1508 | 0.153 | 0.157 | 0.155 | 0.035 | 0.122 | 0.078 | |
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| 0.3467 | 0.6 | 3000 | 0.1397 | 0.14 | 0.258 | 0.199 | 0.033 | 0.213 | 0.123 | |
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| 0.3443 | 0.7 | 3500 | 0.1333 | 0.139 | 0.044 | 0.092 | 0.032 | 0.027 | 0.029 | |
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| 0.3169 | 0.8 | 4000 | 0.1297 | 0.129 | 0.027 | 0.078 | 0.029 | 0.011 | 0.02 | |
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| 0.3276 | 0.9 | 4500 | 0.1264 | 0.124 | 0.086 | 0.105 | 0.028 | 0.058 | 0.043 | |
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| 0.317 | 1.0 | 5000 | 0.1255 | 0.124 | 0.171 | 0.147 | 0.028 | 0.164 | 0.096 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.2.0 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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