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---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
- automatic-speech-recognition
- natbed
- generated_from_trainer
metrics:
- wer
model-index:
- name: xls-r-1b-bem-natbed-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-bem-natbed-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 NATBED - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7801
- Wer: 0.7879
## 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 | 0.1252 | 100 | 1.3725 | 0.9805 |
| No log | 0.2505 | 200 | 0.9491 | 0.8541 |
| No log | 0.3757 | 300 | 0.9524 | 0.8137 |
| No log | 0.5009 | 400 | 1.0355 | 0.9016 |
| 1.7945 | 0.6262 | 500 | 0.9611 | 0.8788 |
| 1.7945 | 0.7514 | 600 | 0.9790 | 0.8642 |
| 1.7945 | 0.8766 | 700 | 0.9877 | 0.8602 |
| 1.7945 | 1.0019 | 800 | 0.9604 | 0.8925 |
| 1.7945 | 1.1271 | 900 | 0.8880 | 0.8328 |
| 0.9885 | 1.2523 | 1000 | 0.8917 | 0.8368 |
| 0.9885 | 1.3776 | 1100 | 0.9034 | 0.8306 |
| 0.9885 | 1.5028 | 1200 | 0.8478 | 0.7938 |
| 0.9885 | 1.6281 | 1300 | 0.8666 | 0.8628 |
| 0.9885 | 1.7533 | 1400 | 0.8331 | 0.8218 |
| 0.8854 | 1.8785 | 1500 | 0.8405 | 0.8045 |
| 0.8854 | 2.0038 | 1600 | 0.7801 | 0.7879 |
| 0.8854 | 2.1290 | 1700 | 0.8305 | 0.7917 |
| 0.8854 | 2.2542 | 1800 | 0.7972 | 0.7911 |
| 0.8854 | 2.3795 | 1900 | 0.7916 | 0.7758 |
### Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
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