---
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-combined-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-combined-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: 0.7801
- Wer: 0.7879

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log        | 0.1252 | 100  | 1.3725          | 0.9805 |
| No log        | 0.2505 | 200  | 0.9491          | 0.8541 |
| No log        | 0.3757 | 300  | 0.9524          | 0.8137 |
| No log        | 0.5009 | 400  | 1.0355          | 0.9016 |
| 1.7945        | 0.6262 | 500  | 0.9611          | 0.8788 |
| 1.7945        | 0.7514 | 600  | 0.9790          | 0.8642 |
| 1.7945        | 0.8766 | 700  | 0.9877          | 0.8602 |
| 1.7945        | 1.0019 | 800  | 0.9604          | 0.8925 |
| 1.7945        | 1.1271 | 900  | 0.8880          | 0.8328 |
| 0.9885        | 1.2523 | 1000 | 0.8917          | 0.8368 |
| 0.9885        | 1.3776 | 1100 | 0.9034          | 0.8306 |
| 0.9885        | 1.5028 | 1200 | 0.8478          | 0.7938 |
| 0.9885        | 1.6281 | 1300 | 0.8666          | 0.8628 |
| 0.9885        | 1.7533 | 1400 | 0.8331          | 0.8218 |
| 0.8854        | 1.8785 | 1500 | 0.8405          | 0.8045 |
| 0.8854        | 2.0038 | 1600 | 0.7801          | 0.7879 |
| 0.8854        | 2.1290 | 1700 | 0.8305          | 0.7917 |
| 0.8854        | 2.2542 | 1800 | 0.7972          | 0.7911 |
| 0.8854        | 2.3795 | 1900 | 0.7916          | 0.7758 |


### Framework versions

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