---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
- automatic-speech-recognition
- natbed
- generated_from_trainer
metrics:
- wer
model-index:
- name: xls-r-1b-bem-natbed-non-native-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. -->

# xls-r-1b-bem-natbed-non-native-model

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the NATBED - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6818
- Wer: 0.7142

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 30.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 3.8975        | 0.4515 | 100  | 1.1343          | 0.9316 |
| 1.0247        | 0.9029 | 200  | 0.9811          | 0.8826 |
| 0.9631        | 1.3544 | 300  | 0.8108          | 0.7524 |
| 0.8711        | 1.8059 | 400  | 0.7749          | 0.7638 |
| 0.7935        | 2.2573 | 500  | 0.8008          | 0.8232 |
| 0.7869        | 2.7088 | 600  | 0.7334          | 0.7262 |
| 0.7265        | 3.1603 | 700  | 0.7239          | 0.6950 |
| 0.7011        | 3.6117 | 800  | 0.7077          | 0.6807 |
| 0.7343        | 4.0632 | 900  | 0.6985          | 0.6914 |
| 0.6624        | 4.5147 | 1000 | 0.6818          | 0.7142 |
| 0.6642        | 4.9661 | 1100 | 0.7097          | 0.6968 |
| 0.6064        | 5.4176 | 1200 | 0.7195          | 0.6856 |
| 0.5867        | 5.8691 | 1300 | 0.6899          | 0.6880 |


### Framework versions

- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0