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

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the BEMGEN - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3453
- Wer: 0.4416

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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        | 0.3604 | 100  | 3.5018          | 1.0    |
| No log        | 0.7207 | 200  | 2.8616          | 1.0    |
| No log        | 1.0793 | 300  | 1.1005          | 0.9874 |
| No log        | 1.4396 | 400  | 0.6285          | 0.8360 |
| 5.4329        | 1.8    | 500  | 0.5177          | 0.7589 |
| 5.4329        | 2.1586 | 600  | 0.4120          | 0.5989 |
| 5.4329        | 2.5189 | 700  | 0.3998          | 0.5496 |
| 5.4329        | 2.8793 | 800  | 0.3715          | 0.5654 |
| 5.4329        | 3.2378 | 900  | 0.3351          | 0.4872 |
| 0.644         | 3.5982 | 1000 | 0.3334          | 0.5015 |
| 0.644         | 3.9586 | 1100 | 0.3192          | 0.4796 |
| 0.644         | 4.3171 | 1200 | 0.3246          | 0.4594 |
| 0.644         | 4.6775 | 1300 | 0.3242          | 0.4612 |
| 0.644         | 5.0360 | 1400 | 0.3203          | 0.4442 |
| 0.3852        | 5.3964 | 1500 | 0.3453          | 0.4416 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0