---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: MLMA_GPT_Lab8_custom_trained
  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. -->

# MLMA_GPT_Lab8_custom_trained

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1406
- Precision: 0.5275
- Recall: 0.5723
- F1: 0.5490
- Accuracy: 0.9563

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 474  | 0.1706          | 0.4389    | 0.3693 | 0.4011 | 0.9452   |
| 0.2264        | 2.0   | 948  | 0.1624          | 0.4957    | 0.5850 | 0.5367 | 0.9495   |
| 0.1305        | 3.0   | 1422 | 0.1406          | 0.5275    | 0.5723 | 0.5490 | 0.9563   |


### Framework versions

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