transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer ta dataset:mozilla-foundation/common_voice_16_0 base_model:openai/whisper-base license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- ta
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Breeze DSW Tamil - base
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_16_0 ta
      type: mozilla-foundation/common_voice_16_0
      config: ta
      split: test
      args: ta
    metrics:
    - name: Wer
      type: wer
      value: 21.407068619939793
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Breeze DSW Tamil - base

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_16_0 ta dataset.
It achieves the following results on the evaluation set:
- Loss: 0.375
- Wer: 21.4071

## 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
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1698        | 0.1   | 100  | 0.5723          | 30.4406 |
| 0.3578        | 0.2   | 200  | 0.4302          | 25.6862 |
| 0.2832        | 0.3   | 300  | 0.3967          | 23.2048 |
| 0.2663        | 0.4   | 400  | 0.4038          | 23.8525 |
| 0.5175        | 0.5   | 500  | 0.3962          | 24.1466 |
| 0.2365        | 0.6   | 600  | 0.3850          | 22.2595 |
| 0.1692        | 0.7   | 700  | 0.3960          | 21.8687 |
| 0.1815        | 0.8   | 800  | 0.3823          | 22.0772 |
| 0.1612        | 0.9   | 900  | 0.3701          | 21.8056 |
| 0.1393        | 1.0   | 1000 | 0.375           | 21.4071 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
