---
license: apache-2.0
base_model: knowledgator/comprehend_it-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Mongolian_GPT_FakeNews_Comprehendo
  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. -->

# Mongolian_GPT_FakeNews_Comprehendo

This model is a fine-tuned version of [knowledgator/comprehend_it-base](https://huggingface.co/knowledgator/comprehend_it-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3175
- Accuracy: 0.8393

## 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: 16
- eval_batch_size: 3
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1788        | 1.0   | 11   | 0.7540          | 0.8571   |
| 0.2589        | 2.0   | 22   | 0.6399          | 0.8571   |
| 0.1117        | 3.0   | 33   | 0.6795          | 0.8125   |
| 0.0829        | 4.0   | 44   | 0.6606          | 0.8571   |
| 0.0037        | 5.0   | 55   | 0.7375          | 0.8482   |
| 0.0017        | 6.0   | 66   | 0.8388          | 0.8393   |
| 0.0009        | 7.0   | 77   | 0.8872          | 0.8393   |
| 0.0007        | 8.0   | 88   | 0.9371          | 0.8393   |
| 0.0005        | 9.0   | 99   | 0.9949          | 0.8393   |
| 0.0004        | 10.0  | 110  | 1.0329          | 0.8393   |
| 0.0003        | 11.0  | 121  | 1.0626          | 0.8393   |
| 0.0003        | 12.0  | 132  | 1.0800          | 0.8393   |
| 0.0002        | 13.0  | 143  | 1.0993          | 0.8393   |
| 0.0002        | 14.0  | 154  | 1.1330          | 0.8393   |
| 0.0002        | 15.0  | 165  | 1.1925          | 0.8393   |
| 0.0001        | 16.0  | 176  | 1.2286          | 0.8393   |
| 0.0001        | 17.0  | 187  | 1.2468          | 0.8393   |
| 0.0001        | 18.0  | 198  | 1.2586          | 0.8393   |
| 0.0001        | 19.0  | 209  | 1.2686          | 0.8393   |
| 0.0001        | 20.0  | 220  | 1.2758          | 0.8393   |
| 0.0001        | 21.0  | 231  | 1.2836          | 0.8393   |
| 0.0001        | 22.0  | 242  | 1.2914          | 0.8393   |
| 0.0001        | 23.0  | 253  | 1.2978          | 0.8393   |
| 0.0001        | 24.0  | 264  | 1.3027          | 0.8393   |
| 0.0001        | 25.0  | 275  | 1.3070          | 0.8393   |
| 0.0001        | 26.0  | 286  | 1.3106          | 0.8393   |
| 0.0001        | 27.0  | 297  | 1.3131          | 0.8393   |
| 0.0001        | 28.0  | 308  | 1.3156          | 0.8393   |
| 0.0001        | 29.0  | 319  | 1.3170          | 0.8393   |
| 0.0001        | 30.0  | 330  | 1.3175          | 0.8393   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2