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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-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
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