---
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-female-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-female-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: 0.2246
- Wer: 0.3799

## 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 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        | 0.3527 | 100  | 4.0290          | 1.0090 |
| No log        | 0.7055 | 200  | 2.8473          | 1.0    |
| No log        | 1.0564 | 300  | 0.6012          | 0.9269 |
| No log        | 1.4092 | 400  | 0.4191          | 0.8378 |
| 4.9128        | 1.7619 | 500  | 0.3320          | 0.6424 |
| 4.9128        | 2.1129 | 600  | 0.2716          | 0.5178 |
| 4.9128        | 2.4656 | 700  | 0.2724          | 0.4929 |
| 4.9128        | 2.8183 | 800  | 0.2516          | 0.4788 |
| 4.9128        | 3.1693 | 900  | 0.2385          | 0.4438 |
| 0.4407        | 3.5220 | 1000 | 0.2374          | 0.4345 |
| 0.4407        | 3.8748 | 1100 | 0.2354          | 0.4097 |
| 0.4407        | 4.2257 | 1200 | 0.2205          | 0.3961 |
| 0.4407        | 4.5785 | 1300 | 0.2202          | 0.3897 |
| 0.4407        | 4.9312 | 1400 | 0.2246          | 0.3897 |
| 0.2698        | 5.2822 | 1500 | 0.2339          | 0.3666 |
| 0.2698        | 5.6349 | 1600 | 0.2358          | 0.3735 |
| 0.2698        | 5.9877 | 1700 | 0.2246          | 0.3807 |


### Framework versions

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