---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: mitre-gpt2-base
  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. -->

# mitre-gpt2-base

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3404

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 3.2933        | 2.72  | 1000  | 2.6028          |
| 2.2619        | 5.45  | 2000  | 2.4654          |
| 1.9152        | 8.17  | 3000  | 2.3952          |
| 1.6434        | 10.9  | 4000  | 2.3729          |
| 1.4289        | 13.62 | 5000  | 2.4208          |
| 1.2627        | 16.35 | 6000  | 2.4845          |
| 1.1301        | 19.07 | 7000  | 2.5619          |
| 1.0169        | 21.8  | 8000  | 2.6058          |
| 0.93          | 24.52 | 9000  | 2.6773          |
| 0.8587        | 27.25 | 10000 | 2.7389          |
| 0.8032        | 29.97 | 11000 | 2.7639          |
| 0.7506        | 32.7  | 12000 | 2.8329          |
| 0.7079        | 35.42 | 13000 | 2.8934          |
| 0.6781        | 38.15 | 14000 | 2.9175          |
| 0.6461        | 40.87 | 15000 | 2.9532          |
| 0.6205        | 43.6  | 16000 | 3.0008          |
| 0.5987        | 46.32 | 17000 | 3.0539          |
| 0.5811        | 49.05 | 18000 | 3.0738          |
| 0.564         | 51.77 | 19000 | 3.0972          |
| 0.5491        | 54.5  | 20000 | 3.1341          |
| 0.5377        | 57.22 | 21000 | 3.1558          |
| 0.5255        | 59.95 | 22000 | 3.1723          |
| 0.516         | 62.67 | 23000 | 3.1984          |
| 0.5077        | 65.4  | 24000 | 3.2163          |
| 0.5021        | 68.12 | 25000 | 3.2396          |
| 0.4946        | 70.84 | 26000 | 3.2413          |
| 0.4871        | 73.57 | 27000 | 3.2708          |
| 0.4845        | 76.29 | 28000 | 3.2833          |
| 0.4791        | 79.02 | 29000 | 3.2847          |
| 0.4739        | 81.74 | 30000 | 3.2950          |
| 0.4704        | 84.47 | 31000 | 3.3124          |
| 0.4678        | 87.19 | 32000 | 3.3122          |
| 0.4642        | 89.92 | 33000 | 3.3260          |
| 0.4617        | 92.64 | 34000 | 3.3326          |
| 0.4605        | 95.37 | 35000 | 3.3325          |
| 0.4576        | 98.09 | 36000 | 3.3404          |


### Framework versions

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