---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- automatic-speech-recognition
- bemgen
- generated_from_trainer
metrics:
- wer
model-index:
- name: xls-r-300m-bemgen-combined-hp-tuning-test-model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# xls-r-300m-bemgen-combined-hp-tuning-test-model

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the BEMGEN - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3925
- Wer: 0.4224

## 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: 0.0005819322340474784
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- 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        | 2.7986  | 100  | 2.9112          | 1.0    |
| No log        | 5.5704  | 200  | 1.6968          | 0.9971 |
| No log        | 8.3422  | 300  | 0.3893          | 0.6158 |
| No log        | 11.1141 | 400  | 0.3453          | 0.5107 |
| 31.2339       | 13.9127 | 500  | 0.3384          | 0.4909 |
| 31.2339       | 16.6845 | 600  | 0.3592          | 0.4619 |
| 31.2339       | 19.4563 | 700  | 0.3676          | 0.4336 |
| 31.2339       | 22.2282 | 800  | 0.3925          | 0.4228 |


### Framework versions

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