metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: output
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: PolyAI/minds14
type: PolyAI/minds14
config: en-US
split: train
args: en-US
metrics:
- name: Wer
type: wer
value: 0.3191881918819188
output
This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5336
- Wer Ortho: 0.3166
- Wer: 0.3192
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 15
- training_steps: 90
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 2.9987 | 0.5172 | 15 | 1.7184 | 0.4640 | 0.4170 |
| 0.7514 | 1.0345 | 30 | 0.5257 | 0.3790 | 0.3795 |
| 0.307 | 1.5517 | 45 | 0.5051 | 0.3269 | 0.3253 |
| 0.3075 | 2.0690 | 60 | 0.4907 | 0.3526 | 0.3518 |
| 0.1492 | 2.5862 | 75 | 0.5120 | 0.3095 | 0.3106 |
| 0.0719 | 3.1034 | 90 | 0.5336 | 0.3166 | 0.3192 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1