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# ./hamsa-v0.6Q

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the nadsoft/arabic-98 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2781
- Wer: 23.4124

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 300
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.9225        | 0.33  | 100  | 0.8743          | 24.5136 |
| 0.2721        | 0.67  | 200  | 0.2782          | 24.1367 |
| 0.2474        | 1.0   | 300  | 0.2781          | 23.4124 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0

{"language": ["ar"], "license": "apache-2.0", "tags": ["nadsoft", "generated_from_trainer"], "datasets": ["nadsoft/arabic-98"], "metrics": ["wer"], "base_model": "openai/whisper-medium", "model-index": [{"name": "./hamsa-v0.6Q", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "nadsoft/arabic-98", "type": "nadsoft/arabic-98"}, "metrics": [{"type": "wer", "value": 23.412419116812348, "name": "Wer"}]}]}]}
transformers tensorboard safetensors whisper automatic-speech-recognition nadsoft generated_from_trainer ar dataset:nadsoft/arabic-98 base_model:openai/whisper-medium license:apache-2.0 model-index endpoints_compatible region:us