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# hubert-base-libri-pruning-FINAL-TEST2

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1261
- Wer: 0.1114

## 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: 5e-05
- train_batch_size: 64
- 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: 1000
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0609        | 1.12  | 500  | 0.1243          | 0.1111 |
| 0.0579        | 2.24  | 1000 | 0.1242          | 0.1112 |
| 0.0557        | 3.36  | 1500 | 0.1237          | 0.1112 |
| 0.0582        | 4.48  | 2000 | 0.1242          | 0.1112 |
| 0.0507        | 5.61  | 2500 | 0.1247          | 0.1112 |
| 0.0451        | 6.73  | 3000 | 0.1251          | 0.1113 |
| 0.0472        | 7.85  | 3500 | 0.1256          | 0.1114 |
| 0.048         | 8.97  | 4000 | 0.1261          | 0.1114 |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1
- Datasets 2.12.1.dev0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "hubert-base-libri-pruning-FINAL-TEST2", "results": []}]}
transformers pytorch hubert automatic-speech-recognition generated_from_trainer endpoints_compatible region:us