metadata
license: apache-2.0
base_model: arun100/whisper-base-hi-3
tags:
- generated_from_trainer
datasets:
- common_voice_16_0
metrics:
- wer
model-index:
- name: arun100/whisper-base-hi-3
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_16_0
type: common_voice_16_0
config: hi
split: test
args: hi
metrics:
- name: Wer
type: wer
value: 28.586337166830166
arun100/whisper-base-hi-3
This model is a fine-tuned version of arun100/whisper-base-hi-3 on the common_voice_16_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5734
- Wer: 28.5863
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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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 |
|---|---|---|---|---|
| 0.1251 | 13.16 | 1000 | 0.4681 | 27.6638 |
| 0.0812 | 26.32 | 2000 | 0.5046 | 28.2065 |
| 0.0584 | 39.47 | 3000 | 0.5393 | 28.3046 |
| 0.0441 | 52.63 | 4000 | 0.5639 | 28.4924 |
| 0.0392 | 65.79 | 5000 | 0.5734 | 28.5863 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0