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# whisper-base-mixedv1.6

This model was trained from scratch on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2977
- Cer: 8.4783

## 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: 2.5e-05
- train_batch_size: 2
- 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0254        | 8.85  | 1000 | 0.2705          | 9.6739  |
| 0.0001        | 17.7  | 2000 | 0.2947          | 10.2174 |
| 0.0006        | 26.55 | 3000 | 0.2948          | 8.8587  |
| 0.0           | 35.4  | 4000 | 0.2977          | 8.4783  |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.1
- Datasets 2.15.0
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "datasets": ["audiofolder"], "model-index": [{"name": "whisper-base-mixedv1.6", "results": []}]}
transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer dataset:audiofolder endpoints_compatible region:us