metadata
language:
- hi
license: apache-2.0
base_model: arun100/whisper-small-derived-hi-1
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Base Bengali
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_16_0 hi
type: mozilla-foundation/common_voice_16_0
config: hi
split: test
args: hi
metrics:
- name: Wer
type: wer
value: 9.288054935192335
Whisper Base Bengali
This model is a fine-tuned version of arun100/whisper-small-derived-hi-1 on the mozilla-foundation/common_voice_16_0 hi dataset. It achieves the following results on the evaluation set:
- Loss: 0.1458
- Wer: 9.2881
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: 5e-07
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- 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: 20
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1368 | 1.02 | 100 | 0.1665 | 9.6951 |
| 0.1196 | 2.05 | 200 | 0.1586 | 9.6011 |
| 0.107 | 3.07 | 300 | 0.1538 | 9.4008 |
| 0.1051 | 5.02 | 400 | 0.1504 | 9.3235 |
| 0.0988 | 6.05 | 500 | 0.1486 | 9.4467 |
| 0.0939 | 7.07 | 600 | 0.1474 | 9.4425 |
| 0.0901 | 9.02 | 700 | 0.1464 | 9.3006 |
| 0.0859 | 10.04 | 800 | 0.1459 | 9.4362 |
| 0.0859 | 11.07 | 900 | 0.1458 | 9.2881 |
| 0.0839 | 13.02 | 1000 | 0.1456 | 9.2901 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0