metadata
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
- generated_from_trainer
datasets:
- tedlium
metrics:
- wer
model-index:
- name: whisper-tiny-openslrdev
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: tedlium
type: tedlium
config: release1
split: test
args: release1
metrics:
- name: Wer
type: wer
value: 90.4153910381297
whisper-tiny-openslrdev
This model is a fine-tuned version of openai/whisper-tiny.en on the tedlium dataset. It achieves the following results on the evaluation set:
- Loss: 2.0820
- Wer: 90.4154
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 300
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0.06 | 20 | 3.7027 | 35.3291 |
| 3.9098 | 0.13 | 40 | 3.3264 | 35.0647 |
| 3.0852 | 0.19 | 60 | 2.9769 | 34.0871 |
| 2.2682 | 0.26 | 80 | 2.7802 | 31.6309 |
| 1.6662 | 0.32 | 100 | 2.5284 | 27.7728 |
| 1.6662 | 0.38 | 120 | 2.4481 | 24.3668 |
| 1.2505 | 0.45 | 140 | 2.4118 | 21.6532 |
| 1.0859 | 0.51 | 160 | 2.3687 | 20.9087 |
| 0.9491 | 0.58 | 180 | 2.1924 | 19.6493 |
| 0.8746 | 0.64 | 200 | 2.1752 | 22.1229 |
| 0.8746 | 0.7 | 220 | 2.2546 | 29.7245 |
| 0.8064 | 0.77 | 240 | 2.1611 | 39.6326 |
| 0.733 | 0.83 | 260 | 2.1281 | 55.7334 |
| 0.7135 | 0.89 | 280 | 2.0406 | 75.1705 |
| 0.6806 | 0.96 | 300 | 2.0820 | 90.4154 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2