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

# python-gpt2

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: 2.1448

## 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: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 9.2956        | 0.0138 | 25   | 7.9483          |
| 6.8319        | 0.0275 | 50   | 6.0463          |
| 5.653         | 0.0413 | 75   | 5.3905          |
| 5.0998        | 0.0551 | 100  | 5.0523          |
| 4.7296        | 0.0688 | 125  | 4.7295          |
| 4.4676        | 0.0826 | 150  | 4.4801          |
| 4.2285        | 0.0964 | 175  | 4.2580          |
| 4.0335        | 0.1101 | 200  | 4.0891          |
| 3.8654        | 0.1239 | 225  | 3.9376          |
| 3.7442        | 0.1377 | 250  | 3.8222          |
| 3.6155        | 0.1514 | 275  | 3.7006          |
| 3.4805        | 0.1652 | 300  | 3.5997          |
| 3.3804        | 0.1790 | 325  | 3.4840          |
| 3.3074        | 0.1927 | 350  | 3.3887          |
| 3.1737        | 0.2065 | 375  | 3.2711          |
| 3.0593        | 0.2203 | 400  | 3.1535          |
| 2.9634        | 0.2340 | 425  | 3.0443          |
| 2.887         | 0.2478 | 450  | 2.9574          |
| 2.7808        | 0.2616 | 475  | 2.8775          |
| 2.7117        | 0.2753 | 500  | 2.8190          |
| 2.6611        | 0.2891 | 525  | 2.7515          |
| 2.6141        | 0.3029 | 550  | 2.7097          |
| 2.5752        | 0.3167 | 575  | 2.6704          |
| 2.5038        | 0.3304 | 600  | 2.6307          |
| 2.4852        | 0.3442 | 625  | 2.6004          |
| 2.4638        | 0.3580 | 650  | 2.5696          |
| 2.4362        | 0.3717 | 675  | 2.5343          |
| 2.3896        | 0.3855 | 700  | 2.5131          |
| 2.3669        | 0.3993 | 725  | 2.4886          |
| 2.3174        | 0.4130 | 750  | 2.4695          |
| 2.3152        | 0.4268 | 775  | 2.4478          |
| 2.2916        | 0.4406 | 800  | 2.4271          |
| 2.2743        | 0.4543 | 825  | 2.4166          |
| 2.2555        | 0.4681 | 850  | 2.3959          |
| 2.2545        | 0.4819 | 875  | 2.3794          |
| 2.2291        | 0.4956 | 900  | 2.3645          |
| 2.2032        | 0.5094 | 925  | 2.3499          |
| 2.1842        | 0.5232 | 950  | 2.3382          |
| 2.1505        | 0.5369 | 975  | 2.3263          |
| 2.1668        | 0.5507 | 1000 | 2.3147          |
| 2.1649        | 0.5645 | 1025 | 2.3072          |
| 2.1427        | 0.5782 | 1050 | 2.2926          |
| 2.1051        | 0.5920 | 1075 | 2.2799          |
| 2.0792        | 0.6058 | 1100 | 2.2708          |
| 2.1171        | 0.6195 | 1125 | 2.2570          |
| 2.1012        | 0.6333 | 1150 | 2.2470          |
| 2.0853        | 0.6471 | 1175 | 2.2405          |
| 2.0786        | 0.6608 | 1200 | 2.2312          |
| 2.0664        | 0.6746 | 1225 | 2.2238          |
| 2.0706        | 0.6884 | 1250 | 2.2183          |
| 2.0557        | 0.7021 | 1275 | 2.2102          |
| 2.0404        | 0.7159 | 1300 | 2.2042          |
| 2.0493        | 0.7297 | 1325 | 2.1978          |
| 2.0373        | 0.7434 | 1350 | 2.1907          |
| 2.0093        | 0.7572 | 1375 | 2.1837          |
| 2.0228        | 0.7710 | 1400 | 2.1819          |
| 2.0147        | 0.7847 | 1425 | 2.1739          |
| 2.0206        | 0.7985 | 1450 | 2.1694          |
| 2.0156        | 0.8123 | 1475 | 2.1671          |
| 2.0126        | 0.8260 | 1500 | 2.1622          |
| 1.9834        | 0.8398 | 1525 | 2.1598          |
| 2.0182        | 0.8536 | 1550 | 2.1558          |
| 1.9876        | 0.8674 | 1575 | 2.1543          |
| 1.9914        | 0.8811 | 1600 | 2.1515          |
| 1.9933        | 0.8949 | 1625 | 2.1498          |
| 1.9945        | 0.9087 | 1650 | 2.1483          |
| 1.9733        | 0.9224 | 1675 | 2.1470          |
| 1.9778        | 0.9362 | 1700 | 2.1467          |
| 1.983         | 0.9500 | 1725 | 2.1454          |
| 1.9716        | 0.9637 | 1750 | 2.1453          |
| 1.9668        | 0.9775 | 1775 | 2.1449          |
| 1.9733        | 0.9913 | 1800 | 2.1448          |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1