---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/nougat-base
tags:
- generated_from_trainer
model-index:
- name: _base_nougat_logs
  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. -->

# _base_nougat_logs

This model is a fine-tuned version of [facebook/nougat-base](https://huggingface.co/facebook/nougat-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4360

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 6
- total_train_batch_size: 48
- 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
- num_epochs: 30

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 2.0261        | 0.9901  | 83   | 1.9705          |
| 1.8445        | 1.9920  | 167  | 1.7617          |
| 1.6923        | 2.9940  | 251  | 1.6539          |
| 1.597         | 3.9960  | 335  | 1.5871          |
| 1.5287        | 4.9980  | 419  | 1.5196          |
| 1.46          | 6.0     | 503  | 1.4804          |
| 1.3647        | 6.9901  | 586  | 1.4360          |
| 1.289         | 7.9920  | 670  | 1.3772          |
| 1.1741        | 8.9940  | 754  | 1.2350          |
| 0.9947        | 9.9960  | 838  | 1.0415          |
| 0.7889        | 10.9980 | 922  | 0.9238          |
| 0.6771        | 12.0    | 1006 | 0.7884          |
| 0.6256        | 12.9901 | 1089 | 0.6646          |
| 0.5402        | 13.9920 | 1173 | 0.6095          |
| 0.5252        | 14.9940 | 1257 | 0.5702          |
| 0.441         | 15.9960 | 1341 | 0.5282          |
| 0.4077        | 16.9980 | 1425 | 0.5030          |
| 0.3841        | 18.0    | 1509 | 0.4855          |
| 0.3762        | 18.9901 | 1592 | 0.4703          |
| 0.3611        | 19.9920 | 1676 | 0.4587          |
| 0.3486        | 20.9940 | 1760 | 0.4486          |
| 0.3679        | 21.9960 | 1844 | 0.4416          |
| 0.3356        | 22.9980 | 1928 | 0.4400          |
| 0.3343        | 24.0    | 2012 | 0.4387          |
| 0.3229        | 24.9901 | 2095 | 0.4410          |
| 0.2928        | 25.9920 | 2179 | 0.4377          |
| 0.3042        | 26.9940 | 2263 | 0.4393          |
| 0.3439        | 27.9960 | 2347 | 0.4353          |
| 0.3286        | 28.9980 | 2431 | 0.4365          |
| 0.353         | 29.7018 | 2490 | 0.4360          |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3