---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: XLS-R_timit_en
  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. -->

# XLS-R_timit_en

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2960
- Wer: 0.2705

## 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: 8
- 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.6358        | 2.01  | 1000  | 0.7983          | 0.7896 |
| 0.6096        | 4.02  | 2000  | 0.2907          | 0.3794 |
| 0.314         | 6.02  | 3000  | 0.2625          | 0.3246 |
| 0.2259        | 8.03  | 4000  | 0.2673          | 0.3058 |
| 0.1771        | 10.04 | 5000  | 0.2518          | 0.2932 |
| 0.1474        | 12.05 | 6000  | 0.2717          | 0.2900 |
| 0.1267        | 14.06 | 7000  | 0.2700          | 0.2821 |
| 0.1069        | 16.06 | 8000  | 0.2941          | 0.2834 |
| 0.0991        | 18.07 | 9000  | 0.3021          | 0.2806 |
| 0.0853        | 20.08 | 10000 | 0.3088          | 0.2803 |
| 0.0787        | 22.09 | 11000 | 0.2987          | 0.2770 |
| 0.067         | 24.1  | 12000 | 0.3182          | 0.2734 |
| 0.0652        | 26.1  | 13000 | 0.3117          | 0.2701 |
| 0.0636        | 28.11 | 14000 | 0.2960          | 0.2705 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.12.1+cu113
- Datasets 1.18.3
- Tokenizers 0.12.1