transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer endpoints_compatible region:us
---
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisperfinetune_modelcheckpointsv2
  results: []
---

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# whisperfinetune_modelcheckpointsv2

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1296
- Wer: 17.1313

## 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: 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 | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0583        | 1.63  | 1000 | 0.1125          | 10.2794 |
| 0.0113        | 3.26  | 2000 | 0.1196          | 15.8164 |
| 0.0049        | 4.89  | 3000 | 0.1249          | 17.3557 |
| 0.0011        | 6.53  | 4000 | 0.1296          | 17.1313 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
