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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-medium |
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tags: |
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- generated_from_trainer |
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datasets: |
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- fsicoli/common_voice_18_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Medium New Train |
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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 18.0 |
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type: fsicoli/common_voice_18_0 |
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metrics: |
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- name: Wer |
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type: wer |
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value: 2.2782892974889872 |
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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 New Train |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 18.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0204 |
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- Wer: 2.2783 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 1000 |
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- training_steps: 8000 |
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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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| 0.2733 | 0.4077 | 1000 | 0.2585 | 32.5924 | |
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| 0.1527 | 0.8153 | 2000 | 0.1246 | 16.7238 | |
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| 0.0655 | 1.2230 | 3000 | 0.0776 | 10.5668 | |
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| 0.0455 | 1.6307 | 4000 | 0.0514 | 6.7675 | |
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| 0.0162 | 2.0383 | 5000 | 0.0353 | 4.4772 | |
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| 0.0129 | 2.4460 | 6000 | 0.0274 | 3.4364 | |
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| 0.0117 | 2.8536 | 7000 | 0.0220 | 2.5110 | |
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| 0.0044 | 3.2613 | 8000 | 0.0204 | 2.2783 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.3.1 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
