---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: XLS-R_Synthesis_ALL_v1
  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_Synthesis_ALL_v1

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1635
- Wer: 0.1696

## 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: 18
- eval_batch_size: 9
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 72
- total_eval_batch_size: 18
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 4.5765        | 1.0   | 2611  | 1.4891          | 0.9957 |
| 0.7865        | 2.0   | 5223  | 0.3830          | 0.4573 |
| 0.4459        | 3.0   | 7834  | 0.2696          | 0.3355 |
| 0.3452        | 4.0   | 10446 | 0.2259          | 0.2741 |
| 0.2932        | 5.0   | 13057 | 0.2103          | 0.2403 |
| 0.2617        | 6.0   | 15669 | 0.1945          | 0.2206 |
| 0.2421        | 7.0   | 18280 | 0.1853          | 0.2170 |
| 0.2285        | 8.0   | 20892 | 0.1780          | 0.2050 |
| 0.2184        | 9.0   | 23503 | 0.1864          | 0.1997 |
| 0.2115        | 10.0  | 26115 | 0.1737          | 0.1980 |
| 0.2048        | 11.0  | 28726 | 0.1703          | 0.1926 |
| 0.195         | 12.0  | 31338 | 0.1830          | 0.1892 |
| 0.1864        | 13.0  | 33949 | 0.1676          | 0.1844 |
| 0.1785        | 14.0  | 36561 | 0.1609          | 0.1770 |
| 0.1727        | 15.0  | 39172 | 0.1690          | 0.1751 |
| 0.1676        | 16.0  | 41784 | 0.1639          | 0.1750 |
| 0.1638        | 17.0  | 44395 | 0.1634          | 0.1751 |
| 0.1594        | 18.0  | 47007 | 0.1659          | 0.1769 |
| 0.1553        | 19.0  | 49618 | 0.1635          | 0.1696 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0