---
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: hubert-base-libri-pruning-TEST15
  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-TEST15

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: -0.1647
- Wer: 0.1120

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.1439        | 1.12  | 500   | 0.1094          | 0.1124 |
| 0.1385        | 2.24  | 1000  | 0.1164          | 0.1121 |
| 0.1382        | 3.36  | 1500  | 0.1255          | 0.1124 |
| 0.1471        | 4.48  | 2000  | 0.1223          | 0.1117 |
| 0.1273        | 5.61  | 2500  | 0.0958          | 0.1121 |
| 0.0876        | 6.73  | 3000  | 0.0712          | 0.1120 |
| 0.067         | 7.85  | 3500  | 0.0461          | 0.1121 |
| 0.0502        | 8.97  | 4000  | 0.0251          | 0.1119 |
| 0.0279        | 10.09 | 4500  | 0.0051          | 0.1123 |
| -0.003        | 11.21 | 5000  | -0.0139         | 0.1123 |
| -0.016        | 12.33 | 5500  | -0.0303         | 0.1117 |
| -0.0375       | 13.45 | 6000  | -0.0479         | 0.1118 |
| -0.0515       | 14.57 | 6500  | -0.0630         | 0.1124 |
| -0.0578       | 15.7  | 7000  | -0.0768         | 0.1123 |
| -0.0727       | 16.82 | 7500  | -0.0911         | 0.1123 |
| -0.0854       | 17.94 | 8000  | -0.1032         | 0.1123 |
| -0.0987       | 19.06 | 8500  | -0.1132         | 0.1123 |
| -0.1018       | 20.18 | 9000  | -0.1225         | 0.1122 |
| -0.1129       | 21.3  | 9500  | -0.1321         | 0.1123 |
| -0.1252       | 22.42 | 10000 | -0.1399         | 0.1121 |
| -0.1237       | 23.54 | 10500 | -0.1468         | 0.1120 |
| -0.1316       | 24.66 | 11000 | -0.1523         | 0.1122 |
| -0.1317       | 25.78 | 11500 | -0.1571         | 0.1120 |
| -0.1445       | 26.91 | 12000 | -0.1610         | 0.1123 |
| -0.1393       | 28.03 | 12500 | -0.1635         | 0.1120 |
| -0.1453       | 29.15 | 13000 | -0.1647         | 0.1120 |


### Framework versions

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