---
base_model: openai/whisper-large-v3
datasets:
- google/fleurs
library_name: transformers
license: apache-2.0
metrics:
- wer
model-index:
- name: whisper-large-v3-Bengali-Version1
  results: []
language:
- bn
pipeline_tag: automatic-speech-recognition
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# whisper-large-v3-Bengali-Version1

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1519
- Wer: 44.5003

## 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: 3e-06
- train_batch_size: 8
- 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: 1000
- training_steps: 20000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Wer     |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| 0.2412        | 4.8193  | 2000  | 0.2103          | 56.7927 |
| 0.208         | 9.6386  | 4000  | 0.1844          | 51.9640 |
| 0.195         | 14.4578 | 6000  | 0.1719          | 49.3167 |
| 0.194         | 19.2771 | 8000  | 0.1647          | 47.7358 |
| 0.1762        | 24.0964 | 10000 | 0.1597          | 46.6144 |
| 0.1763        | 28.9157 | 12000 | 0.1567          | 45.8361 |
| 0.168         | 33.7349 | 14000 | 0.1544          | 45.1192 |
| 0.1623        | 38.5542 | 16000 | 0.1530          | 44.8802 |
| 0.1601        | 43.3735 | 18000 | 0.1521          | 44.7822 |
| 0.1666        | 48.1928 | 20000 | 0.1519          | 44.5003 |


### Framework versions

- PEFT 0.12.1.dev0
- Transformers 4.45.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1