---
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: hubert-base-libri-pruning-TEST6
  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-TEST6

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: -0.1778
- Wer: 0.1113

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0811        | 1.12  | 500   | 0.1186          | 0.1113 |
| 0.0736        | 2.24  | 1000  | 0.1194          | 0.1114 |
| 0.0721        | 3.36  | 1500  | 0.1197          | 0.1115 |
| 0.0714        | 4.48  | 2000  | 0.1127          | 0.1114 |
| 0.045         | 5.61  | 2500  | 0.0819          | 0.1114 |
| 0.011         | 6.73  | 3000  | 0.0554          | 0.1113 |
| -0.0114       | 7.85  | 3500  | 0.0316          | 0.1112 |
| -0.0312       | 8.97  | 4000  | 0.0121          | 0.1114 |
| -0.0488       | 10.09 | 4500  | -0.0078         | 0.1115 |
| -0.0767       | 11.21 | 5000  | -0.0271         | 0.1113 |
| -0.0882       | 12.33 | 5500  | -0.0439         | 0.1112 |
| -0.1142       | 13.45 | 6000  | -0.0604         | 0.1114 |
| -0.1255       | 14.57 | 6500  | -0.0751         | 0.1113 |
| -0.1383       | 15.7  | 7000  | -0.0885         | 0.1115 |
| -0.1518       | 16.82 | 7500  | -0.1019         | 0.1111 |
| -0.1646       | 17.94 | 8000  | -0.1137         | 0.1114 |
| -0.1723       | 19.06 | 8500  | -0.1247         | 0.1114 |
| -0.178        | 20.18 | 9000  | -0.1343         | 0.1113 |
| -0.1926       | 21.3  | 9500  | -0.1432         | 0.1114 |
| -0.2006       | 22.42 | 10000 | -0.1507         | 0.1114 |
| -0.2029       | 23.54 | 10500 | -0.1581         | 0.1113 |
| -0.2081       | 24.66 | 11000 | -0.1645         | 0.1112 |
| -0.2054       | 25.78 | 11500 | -0.1698         | 0.1111 |
| -0.2153       | 26.91 | 12000 | -0.1738         | 0.1112 |
| -0.2111       | 28.03 | 12500 | -0.1764         | 0.1112 |
| -0.2175       | 29.15 | 13000 | -0.1778         | 0.1113 |


### Framework versions

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