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---
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
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