---
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-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-bemgen-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 BEMGEN - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2509
- Wer: 0.3923

## 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        | 0.1784 | 100  | 3.4413          | 1.0003 |
| No log        | 0.3568 | 200  | 2.9149          | 1.0    |
| No log        | 0.5352 | 300  | 0.7768          | 0.9235 |
| No log        | 0.7136 | 400  | 0.6057          | 0.9047 |
| 5.3372        | 0.8921 | 500  | 0.4317          | 0.6720 |
| 5.3372        | 1.0696 | 600  | 0.3997          | 0.6704 |
| 5.3372        | 1.2480 | 700  | 0.3611          | 0.6405 |
| 5.3372        | 1.4264 | 800  | 0.3441          | 0.5603 |
| 5.3372        | 1.6048 | 900  | 0.2945          | 0.4914 |
| 0.6459        | 1.7832 | 1000 | 0.3041          | 0.4924 |
| 0.6459        | 1.9616 | 1100 | 0.2805          | 0.4681 |
| 0.6459        | 2.1392 | 1200 | 0.2774          | 0.5108 |
| 0.6459        | 2.3176 | 1300 | 0.2683          | 0.4254 |
| 0.6459        | 2.4960 | 1400 | 0.2644          | 0.4382 |
| 0.4599        | 2.6744 | 1500 | 0.2446          | 0.4142 |
| 0.4599        | 2.8528 | 1600 | 0.2473          | 0.4118 |
| 0.4599        | 3.0303 | 1700 | 0.2492          | 0.3961 |
| 0.4599        | 3.2087 | 1800 | 0.2467          | 0.4070 |
| 0.4599        | 3.3872 | 1900 | 0.2509          | 0.3923 |


### Framework versions

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