---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
- automatic-speech-recognition
- genbed
- generated_from_trainer
metrics:
- wer
model-index:
- name: xls-r-1b-bem-genbed-all
  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-genbed-all

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the GENBED - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2172
- Wer: 0.7294

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- 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: 5.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 4.6827        | 0.2644 | 200  | 2.8347          | 1.0    |
| 1.0401        | 0.5288 | 400  | 0.5636          | 0.9410 |
| 0.4289        | 0.7931 | 600  | 0.4018          | 0.9029 |
| 0.3449        | 1.0575 | 800  | 0.3604          | 0.8771 |
| 0.2954        | 1.3219 | 1000 | 0.3389          | 0.8741 |
| 0.2719        | 1.5863 | 1200 | 0.2962          | 0.8439 |
| 0.2472        | 1.8506 | 1400 | 0.2701          | 0.8053 |
| 0.2093        | 2.1150 | 1600 | 0.2599          | 0.8285 |
| 0.1725        | 2.3794 | 1800 | 0.2534          | 0.8375 |
| 0.1675        | 2.6438 | 2000 | 0.2406          | 0.7691 |
| 0.1632        | 2.9081 | 2200 | 0.2309          | 0.7616 |
| 0.1295        | 3.1725 | 2400 | 0.2387          | 0.7557 |
| 0.1082        | 3.4369 | 2600 | 0.2275          | 0.7329 |
| 0.1059        | 3.7013 | 2800 | 0.2240          | 0.7329 |
| 0.1049        | 3.9656 | 3000 | 0.2172          | 0.7294 |
| 0.0657        | 4.2300 | 3200 | 0.2320          | 0.7220 |
| 0.059         | 4.4944 | 3400 | 0.2341          | 0.7215 |
| 0.0582        | 4.7588 | 3600 | 0.2316          | 0.7116 |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1