---
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: hubert-base-libri-pruning-TEST13
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hubert-base-libri-pruning-TEST13

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: -0.0766
- Wer: 0.1385

## 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: 0.00015
- 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: 3000
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.1633        | 1.12  | 500   | 0.1342          | 0.1128 |
| 0.1467        | 2.24  | 1000  | 0.1452          | 0.1173 |
| 0.137         | 3.36  | 1500  | 0.1459          | 0.1174 |
| 0.1382        | 4.48  | 2000  | 0.1362          | 0.1172 |
| 0.1123        | 5.61  | 2500  | 0.1036          | 0.1172 |
| 0.0701        | 6.73  | 3000  | 0.0685          | 0.1135 |
| 0.0496        | 7.85  | 3500  | 0.0547          | 0.1172 |
| 0.0329        | 8.97  | 4000  | 0.0333          | 0.1172 |
| 0.0105        | 10.09 | 4500  | 0.0148          | 0.1175 |
| -0.0203       | 11.21 | 5000  | -0.0041         | 0.1171 |
| -0.0334       | 12.33 | 5500  | -0.0208         | 0.1170 |
| -0.0549       | 13.45 | 6000  | -0.0392         | 0.1170 |
| -0.0688       | 14.57 | 6500  | -0.0535         | 0.1170 |
| -0.0751       | 15.7  | 7000  | -0.0670         | 0.1170 |
| -0.09         | 16.82 | 7500  | -0.0816         | 0.1169 |
| -0.1026       | 17.94 | 8000  | -0.0919         | 0.1177 |
| -0.1161       | 19.06 | 8500  | -0.1012         | 0.1176 |
| -0.1192       | 20.18 | 9000  | -0.1104         | 0.1176 |
| -0.1303       | 21.3  | 9500  | -0.0413         | 0.1386 |
| -0.1426       | 22.42 | 10000 | -0.0510         | 0.1389 |
| -0.141        | 23.54 | 10500 | -0.0576         | 0.1385 |
| -0.1489       | 24.66 | 11000 | -0.0637         | 0.1386 |
| -0.1492       | 25.78 | 11500 | -0.0681         | 0.1386 |
| -0.1619       | 26.91 | 12000 | -0.0728         | 0.1383 |
| -0.1567       | 28.03 | 12500 | -0.0755         | 0.1384 |
| -0.1627       | 29.15 | 13000 | -0.0766         | 0.1385 |


### Framework versions

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