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--- |
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library_name: transformers |
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license: mit |
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base_model: openai/whisper-large-v3-turbo |
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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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model-index: |
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- name: whisper-large-v3-turbo-gl-en |
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results: [] |
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datasets: |
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- juanjucm/OpenSLR-SpeechT-GL-EN |
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language: |
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- gl |
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- en |
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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-v3-turbo-gl-en |
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This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on [juanjucm/OpenSLR-SpeechT-GL-EN](https://huggingface.co/datasets/juanjucm/OpenSLR-SpeechT-GL-EN). |
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It achieves the following results on the test set: |
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- Loss: 0.9360 |
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- Bleu: 55.6535 |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-06 |
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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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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 16 |
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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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- training_steps: 3500 |
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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 | |
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|:-------------:|:-------:|:----:|:---------------:|:-------:| |
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| 0.2758 | 1.6667 | 250 | 0.7646 | 50.6055 | |
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| 0.0592 | 3.3333 | 500 | 0.7730 | 53.1258 | |
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| 0.0406 | 5.0 | 750 | 0.7860 | 53.3406 | |
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| 0.0173 | 6.6667 | 1000 | 0.8358 | 51.9789 | |
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| 0.0091 | 8.3333 | 1250 | 0.8909 | 54.4806 | |
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| 0.0071 | 10.0 | 1500 | 0.8862 | 54.2655 | |
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| 0.0039 | 11.6667 | 1750 | 0.9216 | 52.5119 | |
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| 0.0014 | 13.3333 | 2000 | 0.9281 | 54.5752 | |
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| 0.0013 | 15.0 | 2250 | 0.9471 | 54.5791 | |
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| 0.0009 | 16.6667 | 2500 | 0.9541 | 54.8725 | |
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| 0.0006 | 18.3333 | 2750 | 0.9614 | 53.1879 | |
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| 0.0006 | 20.0 | 3000 | 0.9701 | 54.6499 | |
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| 0.0006 | 21.6667 | 3250 | 0.9739 | 54.4341 | |
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| 0.0006 | 23.3333 | 3500 | 0.9747 | 54.5311 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
