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---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- bleu
- wer
model-index:
- name: Whisper Small GA-EN Speech Translation
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Small GA-EN Speech Translation
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4049
- Bleu: 26.13
- Chrf: 43.65
- Wer: 76.9923
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.03
- training_steps: 1500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Bleu | Chrf | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:-----:|:-----:|:---------------:|:--------:|
| 2.2789 | 0.11 | 100 | 9.07 | 25.39 | 2.0838 | 102.2963 |
| 1.9858 | 0.22 | 200 | 12.68 | 29.42 | 1.7854 | 101.1706 |
| 1.6904 | 0.32 | 300 | 11.93 | 31.4 | 1.6522 | 148.2215 |
| 1.4934 | 0.43 | 400 | 16.44 | 35.2 | 1.5699 | 95.3174 |
| 1.371 | 0.54 | 500 | 15.89 | 34.46 | 1.5181 | 100.9455 |
| 1.1806 | 0.65 | 600 | 20.62 | 40.11 | 1.4475 | 91.8955 |
| 1.0781 | 0.76 | 700 | 18.55 | 40.22 | 1.4067 | 99.5948 |
| 0.9166 | 0.86 | 800 | 26.87 | 43.16 | 1.4104 | 71.3192 |
| 0.848 | 0.97 | 900 | 25.95 | 42.61 | 1.3556 | 75.6866 |
| 0.3712 | 1.08 | 1000 | 22.4 | 41.02 | 1.3936 | 87.2580 |
| 0.4415 | 1.19 | 1100 | 1.4157| 28.13 | 43.0 | 68.0324 |
| 0.4166 | 1.29 | 1200 | 1.4206| 27.75 | 44.39 | 71.1391 |
| 0.387 | 1.4 | 1300 | 1.4083| 28.48 | 44.44 | 69.4282 |
| 0.3714 | 1.51 | 1400 | 1.3989| 28.53 | 44.93 | 68.1675 |
| 0.3695 | 1.62 | 1500 | 1.4049| 26.13 | 43.65 | 76.9923 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|