metadata
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- whisper-event
- generated_from_trainer
datasets:
- WillHeld/india_accent_cv
metrics:
- wer
model-index:
- name: Whisper tiny En - Hamna Ramzan
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: South_asian_accent
type: WillHeld/india_accent_cv
metrics:
- name: Wer
type: wer
value: 16.416369438708468
Whisper tiny En - Hamna Ramzan
This model is a fine-tuned version of openai/whisper-tiny on the South_asian_accent dataset. It achieves the following results on the evaluation set:
- Loss: 0.3981
- Wer: 16.4164
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: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|---|---|---|---|---|
| 0.4438 | 0.25 | 1000 | 0.5724 | 23.7751 |
| 0.3441 | 1.1425 | 2000 | 0.4521 | 18.5095 |
| 0.2427 | 2.035 | 3000 | 0.4335 | 18.0589 |
| 0.2993 | 2.285 | 4000 | 0.3981 | 16.4164 |
Framework versions
- Transformers 4.52.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.5.2.dev0
- Tokenizers 0.21.1