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---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
- automatic-speech-recognition
- genbed
- generated_from_trainer
metrics:
- wer
model-index:
- name: xls-r-1b-bem-genbed-f-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-bem-genbed-f-model
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the GENBED - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3137
- Wer: 0.5529
## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 | 0.2740 | 100 | 3.0378 | 1.0 |
| No log | 0.5479 | 200 | 0.8302 | 0.9818 |
| No log | 0.8219 | 300 | 0.6783 | 0.9103 |
| No log | 1.0959 | 400 | 0.5512 | 0.8721 |
| 1.8782 | 1.3699 | 500 | 0.5296 | 0.8568 |
| 1.8782 | 1.6438 | 600 | 0.4413 | 0.7333 |
| 1.8782 | 1.9178 | 700 | 0.4747 | 0.7614 |
| 1.8782 | 2.1918 | 800 | 0.3884 | 0.6667 |
| 1.8782 | 2.4658 | 900 | 0.3577 | 0.6355 |
| 0.5114 | 2.7397 | 1000 | 0.3585 | 0.6321 |
| 0.5114 | 3.0137 | 1100 | 0.3641 | 0.6607 |
| 0.5114 | 3.2877 | 1200 | 0.3813 | 0.7282 |
| 0.5114 | 3.5616 | 1300 | 0.3829 | 0.7086 |
| 0.5114 | 3.8356 | 1400 | 0.3682 | 0.6413 |
| 0.3931 | 4.1096 | 1500 | 0.3527 | 0.6221 |
| 0.3931 | 4.3836 | 1600 | 0.3481 | 0.6297 |
| 0.3931 | 4.6575 | 1700 | 0.3541 | 0.6193 |
| 0.3931 | 4.9315 | 1800 | 0.3355 | 0.6242 |
| 0.3931 | 5.2055 | 1900 | 0.3339 | 0.5801 |
| 0.3293 | 5.4795 | 2000 | 0.3137 | 0.5529 |
| 0.3293 | 5.7534 | 2100 | 0.3132 | 0.5822 |
| 0.3293 | 6.0274 | 2200 | 0.3145 | 0.5676 |
| 0.3293 | 6.3014 | 2300 | 0.3283 | 0.5961 |
| 0.3293 | 6.5753 | 2400 | 0.3247 | 0.5988 |
### Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
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