metadata
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: whisper-small-English
results: []
whisper-small-English
This model is a fine-tuned version of openai/whisper-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4278
- Accuracy: 22.4848
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1469 | 0.4 | 100 | 0.3931 | 20.8666 |
| 0.1704 | 0.8 | 200 | 0.3690 | 20.5089 |
| 0.1317 | 1.2 | 300 | 0.3650 | 20.4210 |
| 0.1323 | 1.6 | 400 | 0.3659 | 21.3649 |
| 0.131 | 2.0 | 500 | 0.3675 | 21.1480 |
| 0.0662 | 2.4 | 600 | 0.4080 | 21.8105 |
| 0.0678 | 2.8 | 700 | 0.3958 | 22.5199 |
| 0.028 | 3.2 | 800 | 0.4290 | 22.0216 |
| 0.0313 | 3.6 | 900 | 0.4195 | 22.4496 |
| 0.032 | 4.0 | 1000 | 0.4278 | 22.4848 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1