---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- timit_asr
model-index:
- name: wav2vec2-xls-r-1b_phoneme-timit_english_timit-4k_001
  results: []
language:
- en
metrics:
- wer
library_name: transformers
pipeline_tag: automatic-speech-recognition
---

<!-- 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. -->

# wav2vec2-xls-r-1b_phoneme-timit_english_timit-4k_001

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the timit dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4353
- Per: 0.1233

## 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: 5000
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Per    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.356         | 1.73  | 1000  | 0.4634          | 0.1786 |
| 0.7615        | 3.46  | 2000  | 0.4203          | 0.1688 |
| 0.6183        | 5.19  | 3000  | 0.4097          | 0.1705 |
| 0.6072        | 6.92  | 4000  | 0.4693          | 0.1798 |
| 0.6144        | 8.65  | 5000  | 0.5058          | 0.1810 |
| 0.5871        | 10.38 | 6000  | 0.4735          | 0.1761 |
| 0.5046        | 12.11 | 7000  | 0.4379          | 0.1654 |
| 0.4093        | 13.84 | 8000  | 0.4333          | 0.1577 |
| 0.3299        | 15.57 | 9000  | 0.4281          | 0.1526 |
| 0.2723        | 17.3  | 10000 | 0.4353          | 0.1499 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.1
- Datasets 2.18.0
- Tokenizers 0.13.3