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# ft_model

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6109
- Cer: 16.9926

## 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: 1
- eval_batch_size: 1
- 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: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3246        | 0.25  | 500  | 0.6696          | 18.6400 |
| 0.3243        | 0.5   | 1000 | 0.6509          | 18.5784 |
| 0.2622        | 0.75  | 1500 | 0.6245          | 17.5366 |
| 0.3307        | 1.0   | 2000 | 0.6109          | 16.9926 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"language": ["ur"], "license": "apache-2.0", "tags": ["hf-asr-leaderboard", "generated_from_trainer"], "datasets": ["common_voice_16_1"], "base_model": "openai/whisper-base", "model-index": [{"name": "ft_model", "results": []}]}
transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer ur dataset:common_voice_16_1 base_model:openai/whisper-base license:apache-2.0 endpoints_compatible region:us