metadata
library_name: peft
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
model-index:
- name: bambara-whisper-large-v5
results: []
bambara-whisper-large-v5
This model is a fine-tuned version of openai/whisper-large-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0897
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 100
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.5664 | 0.2674 | 250 | 2.3071 |
| 1.9725 | 0.5348 | 500 | 2.0162 |
| 1.579 | 0.8021 | 750 | 1.4457 |
| 1.4458 | 1.0695 | 1000 | 1.3399 |
| 1.3508 | 1.3369 | 1250 | 1.2798 |
| 1.3225 | 1.6043 | 1500 | 1.2372 |
| 1.2974 | 1.8717 | 1750 | 1.2088 |
| 1.2617 | 2.1390 | 2000 | 1.1850 |
| 1.2305 | 2.4064 | 2250 | 1.1643 |
| 1.2392 | 2.6738 | 2500 | 1.1466 |
| 1.2395 | 2.9412 | 2750 | 1.1342 |
| 1.1663 | 3.2086 | 3000 | 1.1249 |
| 1.1967 | 3.4759 | 3250 | 1.1139 |
| 1.1624 | 3.7433 | 3500 | 1.1087 |
| 1.1527 | 4.0107 | 3750 | 1.1031 |
| 1.1512 | 4.2781 | 4000 | 1.0985 |
| 1.1589 | 4.5455 | 4250 | 1.0945 |
| 1.1547 | 4.8128 | 4500 | 1.0926 |
| 1.1334 | 5.0802 | 4750 | 1.0919 |
| 1.1688 | 5.3476 | 5000 | 1.0903 |
| 1.1324 | 5.6150 | 5250 | 1.0898 |
| 1.1735 | 5.8824 | 5500 | 1.0897 |
Framework versions
- PEFT 0.14.1.dev0
- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0