---
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-m-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-genbed-m-model

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: 0.5624
- Wer: 0.7514

## 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        | 0.2759 | 100  | 2.9022          | 1.0    |
| No log        | 0.5517 | 200  | 1.4915          | 1.0022 |
| No log        | 0.8276 | 300  | 0.9387          | 0.9416 |
| No log        | 1.1034 | 400  | 0.7254          | 0.8661 |
| 2.1327        | 1.3793 | 500  | 0.8557          | 0.9420 |
| 2.1327        | 1.6552 | 600  | 0.7236          | 0.8662 |
| 2.1327        | 1.9310 | 700  | 0.6982          | 0.8573 |
| 2.1327        | 2.2069 | 800  | 0.6066          | 0.8003 |
| 2.1327        | 2.4828 | 900  | 0.6352          | 0.7989 |
| 0.733         | 2.7586 | 1000 | 0.5855          | 0.7902 |
| 0.733         | 3.0345 | 1100 | 0.5587          | 0.7390 |
| 0.733         | 3.3103 | 1200 | 0.5624          | 0.7514 |
| 0.733         | 3.5862 | 1300 | 0.5214          | 0.7193 |
| 0.733         | 3.8621 | 1400 | 0.5321          | 0.7208 |
| 0.5894        | 4.1379 | 1500 | 0.6477          | 0.7799 |
| 0.5894        | 4.4138 | 1600 | 0.6076          | 0.7810 |
| 0.5894        | 4.6897 | 1700 | 0.5821          | 0.7666 |


### Framework versions

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