metadata
base_model: openai/whisper-large-v3-turbo
library_name: transformers
license: mit
metrics:
- bleu
tags:
- generated_from_trainer
model-index:
- name: ar-eng-autonote-turbo-exp-1
results: []
ar-eng-autonote-turbo-exp-1
This model is a fine-tuned version of openai/whisper-large-v3-turbo on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.5087
- Bleu: 21.2006
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: 5e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|---|---|---|---|---|
| 4.0421 | 1.0 | 147 | 3.1522 | 11.1208 |
| 3.0199 | 2.0 | 294 | 2.7301 | 12.1175 |
| 2.306 | 3.0 | 441 | 2.5164 | 14.4358 |
| 2.0018 | 4.0 | 588 | 2.4287 | 16.7516 |
| 1.6744 | 5.0 | 735 | 2.3919 | 19.6511 |
| 1.5185 | 6.0 | 882 | 2.3922 | 18.5162 |
| 1.3278 | 7.0 | 1029 | 2.4099 | 21.0711 |
| 1.245 | 8.0 | 1176 | 2.4405 | 18.8528 |
| 1.1109 | 9.0 | 1323 | 2.4835 | 20.8498 |
| 0.9965 | 10.0 | 1470 | 2.5087 | 21.2006 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0