README.md

---
language:
- te
license: apache-2.0
base_model: openai/whisper-medium
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- Sonal0205/telugu_asr
metrics:
- wer
model-index:
- name: Whisper Medium te - telugu
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Telugu ASR
      type: Sonal0205/telugu_asr
      args: 'config: te, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 39.00118906064209
---

<!-- 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 Medium te - telugu

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Telugu ASR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1044
- Wer: 39.0012

## 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-05
- train_batch_size: 16
- 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: 500
- training_steps: 4000

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0415        | 2.1142 | 1000 | 0.0918          | 57.5208 |
| 0.0104        | 4.2283 | 2000 | 0.0984          | 38.3769 |
| 0.0023        | 6.3425 | 3000 | 0.1018          | 31.8074 |
| 0.0001        | 8.4567 | 4000 | 0.1044          | 39.0012 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.4.0.dev20240527+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1