---
base_model: facebook/wav2vec2-xls-r-300m
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: xlsr-wav2vec2-model
  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. -->

# xlsr-wav2vec2-model

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7303
- Wer: 0.4284

## 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

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 7.3963        | 2.1834  | 500  | 3.4058          | 1.0    |
| 2.9024        | 4.3668  | 1000 | 3.1374          | 1.0    |
| 2.5161        | 6.5502  | 1500 | 1.4918          | 1.0610 |
| 1.1536        | 8.7336  | 2000 | 0.8087          | 0.6197 |
| 0.7102        | 10.9170 | 2500 | 0.6845          | 0.5452 |
| 0.5177        | 13.1004 | 3000 | 0.6658          | 0.5055 |
| 0.3888        | 15.2838 | 3500 | 0.6185          | 0.4784 |
| 0.3311        | 17.4672 | 4000 | 0.6584          | 0.4690 |
| 0.2776        | 19.6507 | 4500 | 0.6956          | 0.4529 |
| 0.24          | 21.8341 | 5000 | 0.6835          | 0.4510 |
| 0.203         | 24.0175 | 5500 | 0.6903          | 0.4452 |
| 0.1945        | 26.2009 | 6000 | 0.7061          | 0.4332 |
| 0.1627        | 28.3843 | 6500 | 0.7303          | 0.4284 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1