---
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-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-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: 0.6841
- Wer: 0.7487

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 4.5137        | 0.5618 | 100  | 2.5549          | 1.0    |
| 1.3916        | 1.1236 | 200  | 1.0883          | 0.9840 |
| 0.9962        | 1.6854 | 300  | 0.8153          | 0.8190 |
| 0.8625        | 2.2472 | 400  | 0.8690          | 0.8418 |
| 0.8168        | 2.8090 | 500  | 0.7395          | 0.7390 |
| 0.7197        | 3.3708 | 600  | 0.7596          | 0.7366 |
| 0.6848        | 3.9326 | 700  | 0.7033          | 0.7229 |
| 0.6134        | 4.4944 | 800  | 0.8300          | 0.7662 |
| 0.6303        | 5.0562 | 900  | 0.7365          | 0.7896 |
| 0.5467        | 5.6180 | 1000 | 0.6841          | 0.7487 |
| 0.5194        | 6.1798 | 1100 | 0.7868          | 0.6949 |
| 0.4617        | 6.7416 | 1200 | 0.7563          | 0.7278 |
| 0.4525        | 7.3034 | 1300 | 0.7276          | 0.6730 |


### Framework versions

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