metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: openai/whisper-small.en
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: rishabhjain16/infer_myst
type: rishabhjain16/infer_myst
config: en
split: test
metrics:
- type: wer
value: 12.66
name: WER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: rishabhjain16/infer_cmu
type: rishabhjain16/infer_cmu
config: en
split: test
metrics:
- type: wer
value: 10.06
name: WER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: rishabhjain16/libritts_dev_clean
type: rishabhjain16/libritts_dev_clean
config: en
split: test
metrics:
- type: wer
value: 5.53
name: WER
openai/whisper-small.en
This model is a fine-tuned version of openai/whisper-small.en on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5806
- Wer: 12.9802
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: 64
- eval_batch_size: 32
- 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: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1886 | 2.01 | 500 | 0.3621 | 11.9972 |
| 0.187 | 4.03 | 1000 | 0.3786 | 12.3615 |
| 0.0285 | 6.04 | 1500 | 0.4436 | 12.5951 |
| 0.0319 | 8.06 | 2000 | 0.5057 | 12.8262 |
| 0.0044 | 10.07 | 2500 | 0.5620 | 13.1238 |
| 0.0054 | 13.01 | 3000 | 0.5806 | 12.9802 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2