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# whisper-large-updated

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3340
- Wer: 0.0

## 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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 7
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer  |
|:-------------:|:-----:|:----:|:---------------:|:----:|
| No log        | 1.0   | 1    | 2.3340          | 0.0  |
| No log        | 2.0   | 2    | 2.3340          | 0.0  |
| No log        | 3.0   | 3    | 2.3340          | 0.0  |
| No log        | 4.0   | 4    | 2.3340          | 0.0  |
| No log        | 5.0   | 5    | 2.3340          | 0.0  |
| No log        | 6.0   | 6    | 2.0215          | 12.5 |
| No log        | 7.0   | 7    | 1.9111          | 12.5 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "base_model": "openai/whisper-large-v2", "model-index": [{"name": "whisper-large-updated", "results": []}]}
transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer base_model:openai/whisper-large-v2 license:apache-2.0 endpoints_compatible region:us