metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-tiny-akan
results: []
whisper-tiny-akan
This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2466
- Wer: 18.4363
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.8631 | 2.9070 | 250 | 0.8110 | 57.7923 |
| 0.4257 | 5.8140 | 500 | 0.7295 | 50.5545 |
| 0.1859 | 8.7209 | 750 | 0.7882 | 50.0381 |
| 0.0717 | 11.6279 | 1000 | 0.8608 | 49.2847 |
| 0.0758 | 14.5349 | 1250 | 0.2162 | 17.7826 |
| 0.0242 | 17.4419 | 1500 | 0.2390 | 19.1234 |
| 0.0105 | 20.3488 | 1750 | 0.2467 | 19.7519 |
| 0.0054 | 23.2558 | 2000 | 0.2466 | 18.4363 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1