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--- |
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license: apache-2.0 |
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base_model: openai/whisper-medium |
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tags: |
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- generated_from_trainer |
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datasets: |
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- fsicoli/cv16-fleurs |
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- mozilla-foundation/common_voice_16_1 |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-medium-pt-cv16-fleurs |
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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: mozilla-foundation/common_voice_16_1 pt |
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type: mozilla-foundation/common_voice_16_1 |
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args: default |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.09421927983206846 |
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language: |
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- pt |
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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-pt-cv16-fleurs |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the fsicoli/cv16-fleurs default dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1409 |
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- Wer: 0.0942 |
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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-06 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 2 |
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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: 5000 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.2552 | 0.93 | 1000 | 0.2200 | 0.1220 | |
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| 0.1928 | 1.87 | 2000 | 0.1645 | 0.1062 | |
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| 0.1646 | 2.8 | 3000 | 0.1508 | 0.1016 | |
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| 0.1333 | 3.74 | 4000 | 0.1438 | 0.0970 | |
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| 0.1027 | 4.67 | 5000 | 0.1409 | 0.0942 | |
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### Framework versions |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.2.1 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.2 |
