---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: finetune_add_transformer
  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. -->

# finetune_add_transformer

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co./facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2934
- Cer: 0.0724

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Cer    |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 4.2464        | 5.95   | 500   | 0.7569          | 0.2284 |
| 0.5463        | 11.9   | 1000  | 0.3276          | 0.0814 |
| 0.3545        | 17.86  | 1500  | 0.3084          | 0.0779 |
| 0.2841        | 23.81  | 2000  | 0.3200          | 0.0756 |
| 0.232         | 29.76  | 2500  | 0.3181          | 0.0735 |
| 0.1922        | 35.71  | 3000  | 0.3480          | 0.0731 |
| 0.1601        | 41.67  | 3500  | 0.3990          | 0.0742 |
| 0.1362        | 47.62  | 4000  | 0.4304          | 0.0736 |
| 0.1165        | 53.57  | 4500  | 0.4847          | 0.0746 |
| 0.0994        | 59.52  | 5000  | 0.5250          | 0.0761 |
| 0.0876        | 65.48  | 5500  | 0.5628          | 0.0740 |
| 0.0791        | 71.43  | 6000  | 0.5871          | 0.0742 |
| 0.0716        | 77.38  | 6500  | 0.5933          | 0.0729 |
| 0.0661        | 83.33  | 7000  | 0.6238          | 0.0739 |
| 0.0605        | 89.29  | 7500  | 0.6623          | 0.0742 |
| 0.0569        | 95.24  | 8000  | 0.6638          | 0.0729 |
| 0.0535        | 101.19 | 8500  | 0.6681          | 0.0730 |
| 0.0498        | 107.14 | 9000  | 0.6815          | 0.0733 |
| 0.0491        | 113.1  | 9500  | 0.6818          | 0.0733 |
| 0.0471        | 119.05 | 10000 | 0.6810          | 0.0732 |


### Framework versions

- Transformers 4.17.0
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0