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---
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
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