metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: akan-whisper-medium
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: audiofolder
type: audiofolder
config: default
split: train
args: default
metrics:
- name: Wer
type: wer
value: 65.37832712052841
akan-whisper-medium
This model is a fine-tuned version of akan-whisper-medium on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.3225
- Wer: 65.3783
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: 8
- 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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6326 | 7.5758 | 500 | 0.8675 | 71.1922 |
| 0.1649 | 15.1515 | 1000 | 0.8976 | 65.7903 |
| 0.0284 | 22.7273 | 1500 | 1.0661 | 66.8563 |
| 0.0067 | 30.3030 | 2000 | 1.1925 | 66.7517 |
| 0.0034 | 37.8788 | 2500 | 1.2540 | 68.6221 |
| 0.0022 | 45.4545 | 3000 | 1.2904 | 67.0721 |
| 0.0018 | 53.0303 | 3500 | 1.3139 | 67.5038 |
| 0.0017 | 60.6061 | 4000 | 1.3225 | 65.3783 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1