---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-1b-E3
  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. -->

# wav2vec2-1b-E3

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4214
- Cer: 11.5484

## 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: 0.0001
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- 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: 50
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 10.9096       | 0.2580 | 200  | 4.4784          | 97.7502 |
| 2.5397        | 0.5160 | 400  | 1.5540          | 34.0754 |
| 1.2018        | 0.7741 | 600  | 1.1079          | 26.2805 |
| 0.9714        | 1.0321 | 800  | 0.8312          | 20.3360 |
| 0.7789        | 1.2901 | 1000 | 0.7358          | 18.0980 |
| 0.6942        | 1.5481 | 1200 | 0.6558          | 17.2580 |
| 0.6176        | 1.8062 | 1400 | 0.5847          | 15.0787 |
| 0.5476        | 2.0642 | 1600 | 0.5941          | 15.8365 |
| 0.4525        | 2.3222 | 1800 | 0.5006          | 13.3870 |
| 0.4068        | 2.5802 | 2000 | 0.4577          | 12.6527 |
| 0.37          | 2.8383 | 2200 | 0.4214          | 11.5484 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3