---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: hubert-base-libri-demo-feature_extractor_frozen
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# hubert-base-libri-demo-feature_extractor_frozen

This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1217
- Wer: 0.3031

## 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: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 4.446         | 1.12  | 500   | 3.5285          | 0.9999 |
| 2.8792        | 2.24  | 1000  | 3.2540          | 0.9999 |
| 2.8504        | 3.36  | 1500  | 3.0608          | 0.9999 |
| 1.2084        | 4.48  | 2000  | 0.3020          | 0.6763 |
| 0.3281        | 5.61  | 2500  | 0.1665          | 0.4887 |
| 0.2158        | 6.73  | 3000  | 0.1389          | 0.4071 |
| 0.179         | 7.85  | 3500  | 0.1294          | 0.3710 |
| 0.163         | 8.97  | 4000  | 0.1199          | 0.3592 |
| 0.1461        | 10.09 | 4500  | 0.1177          | 0.3485 |
| 0.1138        | 11.21 | 5000  | 0.1120          | 0.3374 |
| 0.1154        | 12.33 | 5500  | 0.1215          | 0.3307 |
| 0.0919        | 13.45 | 6000  | 0.1182          | 0.3279 |
| 0.0911        | 14.57 | 6500  | 0.1194          | 0.3286 |
| 0.0856        | 15.7  | 7000  | 0.1163          | 0.3185 |
| 0.0786        | 16.82 | 7500  | 0.1154          | 0.3193 |
| 0.0738        | 17.94 | 8000  | 0.1124          | 0.3122 |
| 0.0738        | 19.06 | 8500  | 0.1185          | 0.3105 |
| 0.0767        | 20.18 | 9000  | 0.1208          | 0.3061 |
| 0.0664        | 21.3  | 9500  | 0.1211          | 0.3050 |
| 0.0654        | 22.42 | 10000 | 0.1189          | 0.3039 |
| 0.0606        | 23.54 | 10500 | 0.1235          | 0.3041 |
| 0.0584        | 24.66 | 11000 | 0.1217          | 0.3031 |


### Framework versions

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