---
language:
- ta
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Base Ta - Bharat Ramanathan
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0
      type: mozilla-foundation/common_voice_11_0
      config: ta
      split: test
    metrics:
    - type: wer
      value: 15.78
      name: WER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: google/fleurs
      type: google/fleurs
      config: ta_in
      split: test
    metrics:
    - type: wer
      value: 20.41
      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 Ta - Bharat Ramanathan

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2269
- Wer: 21.7243

## 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: 64
- eval_batch_size: 32
- 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.5559        | 0.1   | 1000  | 0.3963          | 35.3308 |
| 0.3891        | 0.2   | 2000  | 0.3146          | 29.1511 |
| 0.3425        | 0.3   | 3000  | 0.2834          | 25.5930 |
| 0.3108        | 0.1   | 4000  | 0.2669          | 24.7191 |
| 0.2866        | 0.1   | 5000  | 0.2596          | 25.0936 |
| 0.2697        | 0.2   | 6000  | 0.2507          | 24.5943 |
| 0.2421        | 0.05  | 6500  | 0.2411          | 23.0395 |
| 0.2425        | 0.1   | 7000  | 0.2370          | 23.3804 |
| 0.2404        | 0.15  | 7500  | 0.2333          | 22.7959 |
| 0.2381        | 0.2   | 8000  | 0.2311          | 22.9420 |
| 0.2429        | 0.25  | 8500  | 0.2305          | 22.0166 |
| 0.2402        | 0.3   | 9000  | 0.2284          | 22.1140 |
| 0.2377        | 0.35  | 9500  | 0.2271          | 22.0653 |
| 0.2389        | 0.4   | 10000 | 0.2269          | 21.7243 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2