transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer ta dataset:mozilla-foundation/common_voice_11_0 base_model:openai/whisper-medium license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- ta
license: apache-2.0
base_model: openai/whisper-medium
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium ta - tamil
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: ta
      split: None
      args: 'config: ta, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 41.13394088172983
---

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# Whisper Medium ta - tamil

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2081
- Wer: 41.1339

## 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.2189        | 0.4202 | 1000 | 0.2631          | 50.3010 |
| 0.1572        | 0.8403 | 2000 | 0.2280          | 45.5056 |
| 0.0873        | 1.2605 | 3000 | 0.2237          | 42.8759 |
| 0.0873        | 1.6807 | 4000 | 0.2081          | 41.1339 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
