metadata
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Hi Test - Kisson
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: hi
split: None
args: 'config: hi, split: test'
metrics:
- name: Wer
type: wer
value: 48.48895284855668
Whisper Small Hi Test - Kisson
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4560
- Wer: 48.4890
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: 5
- training_steps: 40
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3267 | 0.0098 | 4 | 0.4986 | 53.1152 |
| 0.3203 | 0.0196 | 8 | 0.4992 | 52.1544 |
| 0.2772 | 0.0293 | 12 | 0.4968 | 52.0782 |
| 0.303 | 0.0391 | 16 | 0.4895 | 50.7534 |
| 0.3085 | 0.0489 | 20 | 0.4802 | 50.9015 |
| 0.3306 | 0.0587 | 24 | 0.4730 | 50.6222 |
| 0.3181 | 0.0685 | 28 | 0.4664 | 50.1989 |
| 0.3726 | 0.0782 | 32 | 0.4598 | 49.2932 |
| 0.3088 | 0.0880 | 36 | 0.4573 | 48.6202 |
| 0.3347 | 0.0978 | 40 | 0.4560 | 48.4890 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1