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

<!-- 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-large-v3-Assamese-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: 0.2353
- Wer: 62.8123

## 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     |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| 0.3803        | 5.0505  | 2000  | 0.3681          | 78.7302 |
| 0.295         | 10.1010 | 4000  | 0.2985          | 71.4589 |
| 0.277         | 15.1515 | 6000  | 0.2724          | 68.1526 |
| 0.2493        | 20.2020 | 8000  | 0.2586          | 66.3248 |
| 0.2316        | 25.2525 | 10000 | 0.2492          | 64.9954 |
| 0.2236        | 30.3030 | 12000 | 0.2435          | 63.9927 |
| 0.2351        | 35.3535 | 14000 | 0.2401          | 63.2306 |
| 0.2089        | 40.4040 | 16000 | 0.2372          | 62.8295 |
| 0.2205        | 45.4545 | 18000 | 0.2358          | 62.5086 |
| 0.2253        | 50.5051 | 20000 | 0.2353          | 62.8123 |


### 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