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--- |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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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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- chrf |
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model-index: |
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- name: Whisper Base GA-EN Speech Translation |
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results: [] |
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datasets: |
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- ymoslem/IWSLT2023-GA-EN |
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- ymoslem/FLEURS-GA-EN |
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language: |
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- ga |
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- en |
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library_name: transformers |
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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 Base GA-EN Speech Translation |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset. |
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The best model (this version) is at checkpoint 1000, epoch 2.54, and it achieves the following results on the evaluation set: |
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- Loss: 1.9005 |
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- Bleu: 21.83 |
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- Chrf: 37.13 |
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- Wer: 80.4593 |
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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 (v1.1: IWSLT2023-GA-EN; v1.2: +FLEURS-GA-EN) |
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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: 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: 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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| 2.6826 | 0.25 | 100 | 2.0993 | 7.23 | 22.29 | 100.7654 | |
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| 2.1287 | 0.51 | 200 | 1.9451 | 9.37 | 27.74 | 125.9343 | |
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| 1.8482 | 0.76 | 300 | 1.8356 | 13.11 | 30.65 | 103.5570 | |
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| 1.2977 | 1.02 | 400 | 1.8643 | 10.56 | 30.86 | 128.5907 | |
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| 0.8068 | 1.27 | 500 | 1.8658 | 18.23 | 35.17 | 82.6204 | |
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| 0.7257 | 1.52 | 600 | 1.8493 | 17.81 | 34.13 | 90.7249 | |
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| 0.6202 | 1.78 | 700 | 1.8312 | 17.6 | 35.19 | 92.2107 | |
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| 0.4348 | 2.03 | 800 | 1.8771 | 17.9 | 35.66 | 91.9856 | |
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| 0.2566 | 2.28 | 900 | 1.9088 | 20.14 | 36.79 | 81.4498 | |
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| 0.2301 | 2.54 | 1000 | 1.9005 | 21.83 | 37.13 | 80.4593 | |
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### Framework versions |
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- Transformers 4.39.3 |
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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 |
