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---
language:
- bn
license: apache-2.0
base_model: arun100/whisper-base-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 bn
type: mozilla-foundation/common_voice_16_0
config: bn
split: test
args: bn
metrics:
- name: Wer
type: wer
value: 36.204844612672595
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Base Bengali
This model is a fine-tuned version of [arun100/whisper-base-hi-1](https://huggingface.co/arun100/whisper-base-hi-1) on the mozilla-foundation/common_voice_16_0 bn dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2754
- Wer: 36.2048
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.693 | 1.04 | 500 | 0.6937 | 69.6782 |
| 0.3979 | 3.03 | 1000 | 0.4168 | 48.0703 |
| 0.3429 | 5.01 | 1500 | 0.3527 | 42.8105 |
| 0.2907 | 6.05 | 2000 | 0.3225 | 40.4267 |
| 0.2761 | 8.03 | 2500 | 0.3039 | 38.8974 |
| 0.2637 | 10.02 | 3000 | 0.2921 | 37.7927 |
| 0.2507 | 12.0 | 3500 | 0.2846 | 37.0733 |
| 0.2397 | 13.04 | 4000 | 0.2793 | 36.6004 |
| 0.243 | 15.03 | 4500 | 0.2763 | 36.3503 |
| 0.2501 | 17.01 | 5000 | 0.2754 | 36.2048 |
### Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
|