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# Whisper small Hi - CKS 1311 iiitb

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1203
- Wer: 10.8852
- Cer: 3.4179

## 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: 1.75e-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: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
| 0.0291        | 8.77  | 500  | 0.1099          | 14.2344 | 4.1970 |
| 0.004         | 17.54 | 1000 | 0.1114          | 10.8852 | 3.4682 |
| 0.0001        | 26.32 | 1500 | 0.1185          | 10.7656 | 3.3677 |
| 0.0           | 35.09 | 2000 | 0.1203          | 10.8852 | 3.4179 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1

{"language": ["hi"], "license": "apache-2.0", "tags": ["hf-asr-leaderboard", "generated_from_trainer"], "metrics": ["wer"], "base_model": "openai/whisper-medium", "model-index": [{"name": "Whisper small Hi - CKS 1311 iiitb", "results": []}]}
transformers pytorch tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer hi base_model:openai/whisper-medium license:apache-2.0 endpoints_compatible region:us