transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer ml dataset:mozilla-foundation/common_voice_16_0 base_model:openai/whisper-base license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- ml
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 Malayalam - base
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_16_0 ml
      type: mozilla-foundation/common_voice_16_0
      config: ml
      split: test
      args: ml
    metrics:
    - name: Wer
      type: wer
      value: 42.72474513438369
---

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# Breeze DSW Malayalam - 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 ml dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6260
- Wer: 42.7247

## 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: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3151        | 4.02  | 200  | 0.4517          | 54.5134 |
| 0.0703        | 9.02  | 400  | 0.4561          | 46.7285 |
| 0.0144        | 14.02 | 600  | 0.5625          | 43.7627 |
| 0.006         | 19.02 | 800  | 0.6260          | 42.7247 |
| 0.0024        | 24.02 | 1000 | 0.6938          | 43.0306 |
| 0.0012        | 29.02 | 1200 | 0.7354          | 44.2169 |


### Framework versions

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