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--- |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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tags: |
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- generated_from_trainer |
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metrics: |
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- bleu |
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- wer |
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model-index: |
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- name: Whisper Tiny GA-EN Speech Translation |
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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 Tiny GA-EN Speech Translation |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. |
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The best model (this version) is at checkpoint 700, epoch 5.19, and it achieves the following results on the evaluation set: |
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- Loss: 2.7090 |
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- Bleu: 17.56 |
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- Chrf: 32.23 |
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- Wer: 90.4998 |
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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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### Experiment |
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Data Augmentation (processing) |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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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: 0.03 |
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- training_steps: 1000 |
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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 | Bleu | Chrf | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:-----:|:-----:|:--------:| |
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| 0.9302 | 0.74 | 100 | 2.1831 | 8.7 | 24.4 | 114.2729 | |
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| 0.3304 | 1.48 | 200 | 2.2829 | 11.34 | 28.63 | 115.6686 | |
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| 0.1095 | 2.22 | 300 | 2.4409 | 11.35 | 29.53 | 117.4696 | |
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| 0.0781 | 2.96 | 400 | 2.5060 | 12.55 | 29.32 | 110.1306 | |
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| 0.0506 | 3.7 | 500 | 2.6288 | 16.65 | 31.61 | 91.9856 | |
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| 0.041 | 4.44 | 600 | 2.6641 | 15.82 | 31.65 | 96.1279 | |
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| 0.0335 | 5.19 | 700 | 2.7090 | 17.56 | 32.23 | 90.4998 | |
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| 0.0296 | 5.93 | 800 | 2.7257 | 16.61 | 32.11 | 93.0662 | |
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| 0.0278 | 6.67 | 900 | 2.7528 | 15.38 | 31.57 | 95.7226 | |
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| 0.0217 | 7.41 | 1000 | 2.7758 | 15.81 | 32.03 | 96.3980 | |
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### Framework versions |
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- Transformers 4.39.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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