pytorch tensorboard hubert automatic-speech-recognition transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: hubert-large-ls960-ft-timit
  results: []
---

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# hubert-large-ls960-ft-timit

This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co/facebook/hubert-large-ls960-ft) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1074
- Wer: 0.1708

## 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: 0.0001
- train_batch_size: 32
- 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 6.2278        | 4.0   | 500  | 2.6282          | 0.9999 |
| 0.9389        | 8.0   | 1000 | 0.1154          | 0.2096 |
| 0.2005        | 12.0  | 1500 | 0.0951          | 0.1732 |
| 0.1985        | 16.0  | 2000 | 0.0974          | 0.1759 |
| 0.124         | 20.0  | 2500 | 0.0951          | 0.1728 |
| 0.0797        | 24.0  | 3000 | 0.1064          | 0.1713 |
| 0.1047        | 28.0  | 3500 | 0.1074          | 0.1708 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.10.3
