metadata
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
- generated_from_trainer
datasets:
- tedlium
metrics:
- wer
model-index:
- name: whisper-tiny-tedlium
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: 24.245059838575006
whisper-tiny-tedlium
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: 2.2271
- Wer: 24.2451
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: 100
- training_steps: 200
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0.06 | 20 | 3.5590 | 35.2108 |
| 3.8059 | 0.13 | 40 | 3.0962 | 34.2645 |
| 2.6288 | 0.19 | 60 | 2.7592 | 31.2517 |
| 1.688 | 0.26 | 80 | 2.4428 | 24.8330 |
| 1.2352 | 0.32 | 100 | 2.3773 | 22.4951 |
| 1.2352 | 0.38 | 120 | 2.4088 | 21.6219 |
| 0.9947 | 0.45 | 140 | 2.3161 | 19.5345 |
| 0.9169 | 0.51 | 160 | 2.2712 | 23.5736 |
| 0.8418 | 0.58 | 180 | 2.1986 | 23.2918 |
| 0.8253 | 0.64 | 200 | 2.2271 | 24.2451 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2