metadata
library_name: transformers
language:
- ne
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- openslr/openslr
metrics:
- wer
model-index:
- name: Whisper Medium - Kiran Pantha
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: OpenSLR54
type: openslr/openslr
config: default
split: test
args: 'config: ne, split: test'
metrics:
- name: Wer
type: wer
value: 53.889856134884994
Whisper Medium - Kiran Pantha
This model is a fine-tuned version of openai/whisper-tiny on the OpenSLR54 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2728
- Wer: 53.8899
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: 8
- eval_batch_size: 4
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6656 | 0.1200 | 500 | 0.6245 | 85.4211 |
| 0.4586 | 0.2399 | 1000 | 0.4490 | 73.6369 |
| 0.3772 | 0.3599 | 1500 | 0.3930 | 68.5879 |
| 0.3437 | 0.4798 | 2000 | 0.3498 | 63.7222 |
| 0.3214 | 0.5998 | 2500 | 0.3279 | 61.2297 |
| 0.3186 | 0.7198 | 3000 | 0.3095 | 59.3696 |
| 0.2965 | 0.8397 | 3500 | 0.2930 | 56.9504 |
| 0.2759 | 0.9597 | 4000 | 0.2825 | 56.0249 |
| 0.2474 | 1.0797 | 4500 | 0.2758 | 54.5588 |
| 0.2195 | 1.1996 | 5000 | 0.2728 | 53.8899 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1