---
language:
- te
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Base Te - Bharat Ramanathan
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: google/fleurs
      type: google/fleurs
      config: te_in
      split: test
    metrics:
    - type: wer
      value: 39.09
      name: WER
---

<!-- 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 Te - Bharat Ramanathan

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2455
- Wer: 42.6485

## 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: 96
- eval_batch_size: 64
- 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.6341        | 0.1   | 500  | 0.3894          | 60.7108 |
| 0.349         | 0.2   | 1000 | 0.3081          | 52.0935 |
| 0.2792        | 0.3   | 1500 | 0.2874          | 49.7079 |
| 0.2433        | 0.4   | 2000 | 0.2720          | 47.5657 |
| 0.2224        | 1.06  | 2500 | 0.2632          | 45.2288 |
| 0.2058        | 1.16  | 3000 | 0.2529          | 44.3038 |
| 0.1944        | 1.26  | 3500 | 0.2519          | 44.5959 |
| 0.1869        | 1.36  | 4000 | 0.2475          | 43.7196 |
| 0.1811        | 2.03  | 4500 | 0.2451          | 43.3301 |
| 0.1775        | 2.13  | 5000 | 0.2455          | 42.6485 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2