---
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-5hrs
  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-bigcgen-combined-5hrs

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: 0.6944
- Wer: 0.6601

## 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        | 0.4228 | 100  | 3.7787          | 1.0    |
| No log        | 0.8457 | 200  | 2.8642          | 1.0    |
| No log        | 1.2664 | 300  | 1.1326          | 0.9986 |
| No log        | 1.6892 | 400  | 0.8747          | 0.8281 |
| 5.818         | 2.1099 | 500  | 0.7865          | 0.8027 |
| 5.818         | 2.5328 | 600  | 0.6710          | 0.6954 |
| 5.818         | 2.9556 | 700  | 0.7234          | 0.7939 |
| 5.818         | 3.3763 | 800  | 0.6657          | 0.6706 |
| 5.818         | 3.7992 | 900  | 0.6836          | 0.7246 |
| 1.2021        | 4.2199 | 1000 | 0.6894          | 0.6897 |
| 1.2021        | 4.6427 | 1100 | 0.6464          | 0.6642 |
| 1.2021        | 5.0634 | 1200 | 0.6663          | 0.6777 |
| 1.2021        | 5.4863 | 1300 | 0.6701          | 0.6704 |
| 1.2021        | 5.9091 | 1400 | 0.6834          | 0.6899 |
| 0.8307        | 6.3298 | 1500 | 0.6944          | 0.6600 |


### Framework versions

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