---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
- automatic-speech-recognition
- bigcgen
- generated_from_trainer
metrics:
- wer
model-index:
- name: xls-r-1b-bigcgen-combined-15hrs-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-1b-bigcgen-combined-15hrs-model

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the BIGCGEN - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5857
- Wer: 0.6274

## 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

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log        | 0.1410 | 100  | 3.8893          | 1.0    |
| No log        | 0.2821 | 200  | 2.6866          | 1.0    |
| No log        | 0.4231 | 300  | 1.4204          | 1.0    |
| No log        | 0.5642 | 400  | 0.8780          | 0.8847 |
| 5.5784        | 0.7052 | 500  | 0.8821          | 0.9583 |
| 5.5784        | 0.8463 | 600  | 0.6898          | 0.7509 |
| 5.5784        | 0.9873 | 700  | 0.6910          | 0.8690 |
| 5.5784        | 1.1283 | 800  | 0.6632          | 0.6810 |
| 5.5784        | 1.2694 | 900  | 0.6165          | 0.6048 |
| 1.2954        | 1.4104 | 1000 | 0.6006          | 0.6134 |
| 1.2954        | 1.5515 | 1100 | 0.6859          | 0.7684 |
| 1.2954        | 1.6925 | 1200 | 0.5857          | 0.6273 |
| 1.2954        | 1.8336 | 1300 | 0.6305          | 0.6155 |
| 1.2954        | 1.9746 | 1400 | 0.6213          | 0.5856 |
| 1.1582        | 2.1157 | 1500 | 0.5891          | 0.5984 |
| 1.1582        | 2.2567 | 1600 | 0.6606          | 0.7041 |


### Framework versions

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