metadata
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- bleu
- wer
model-index:
- name: Whisper Base GA-EN Speech Translation v.1.2
results: []
Whisper Base GA-EN Speech Translation v.1.2
This model is a fine-tuned version of openai/whisper-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.5231
- Bleu: 19.21
- Chrf: 33.89
- Wer: 86.4025
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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.03
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Chrf | Wer |
|---|---|---|---|---|---|---|
| 0.5607 | 1.48 | 100 | 2.0068 | 13.89 | 29.73 | 102.1612 |
| 0.2227 | 2.96 | 200 | 2.1047 | 19.02 | 32.6 | 83.8361 |
| 0.0613 | 4.44 | 300 | 2.2670 | 20.37 | 34.38 | 82.9806 |
| 0.0491 | 5.93 | 400 | 2.2766 | 18.72 | 35.07 | 84.4665 |
| 0.0292 | 7.41 | 500 | 2.3870 | 19.19 | 33.57 | 85.2769 |
| 0.0307 | 8.89 | 600 | 2.4211 | 17.65 | 33.18 | 89.8244 |
| 0.0195 | 10.37 | 700 | 2.4980 | 19.56 | 33.37 | 83.3859 |
| 0.0165 | 11.85 | 800 | 2.4975 | 19.03 | 33.53 | 85.3219 |
| 0.0113 | 13.33 | 900 | 2.5300 | 18.93 | 33.95 | 85.9072 |
| 0.0097 | 14.81 | 1000 | 2.5231 | 19.21 | 33.89 | 86.4025 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2