---
language:
- ta
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: openai/whisper-tiny
model-index:
- name: Whisper Tiny Ta - Bharat Ramanathan
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: ta
      split: test
      args: ta
    metrics:
    - type: wer
      value: 30.102694404742998
      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: 26.07
      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 Tiny Ta - Bharat Ramanathan

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3096
- Wer: 30.1027

## 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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.5622        | 0.2   | 1000  | 0.4460          | 41.4141 |
| 0.4151        | 0.4   | 2000  | 0.3657          | 35.1390 |
| 0.3727        | 0.6   | 3000  | 0.3417          | 33.1723 |
| 0.3519        | 0.8   | 4000  | 0.3252          | 31.9497 |
| 0.3354        | 1.0   | 5000  | 0.3192          | 31.3997 |
| 0.3492        | 0.1   | 6000  | 0.3283          | 31.6966 |
| 0.3229        | 0.2   | 7000  | 0.3211          | 31.1339 |
| 0.3193        | 0.3   | 8000  | 0.3138          | 30.5161 |
| 0.314         | 0.4   | 9000  | 0.3112          | 30.1832 |
| 0.3087        | 0.5   | 10000 | 0.3096          | 30.1027 |


### Framework versions

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