---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: gpt2-10var
  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. -->

# gpt2-10var

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1102

## 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: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| No log        | 0.04  | 200   | 0.2493          |
| No log        | 0.08  | 400   | 0.3971          |
| 0.4919        | 0.12  | 600   | 0.6197          |
| 0.4919        | 0.16  | 800   | 0.5482          |
| 0.9307        | 0.2   | 1000  | 0.8619          |
| 0.9307        | 0.24  | 1200  | 0.5619          |
| 0.9307        | 0.28  | 1400  | 0.7757          |
| 1.6552        | 0.32  | 1600  | 0.5050          |
| 1.6552        | 0.36  | 1800  | 1.1518          |
| 1.1387        | 0.4   | 2000  | 1.0939          |
| 1.1387        | 0.44  | 2200  | 9.2829          |
| 1.1387        | 0.48  | 2400  | 0.2714          |
| 8.5966        | 0.52  | 2600  | 0.1263          |
| 8.5966        | 0.56  | 2800  | 0.1191          |
| 0.1233        | 0.6   | 3000  | 0.1161          |
| 0.1233        | 0.64  | 3200  | 0.1150          |
| 0.1233        | 0.67  | 3400  | 0.1145          |
| 0.1166        | 0.71  | 3600  | 0.1138          |
| 0.1166        | 0.75  | 3800  | 0.1135          |
| 0.1151        | 0.79  | 4000  | 0.1132          |
| 0.1151        | 0.83  | 4200  | 0.1130          |
| 0.1151        | 0.87  | 4400  | 0.1125          |
| 0.1131        | 0.91  | 4600  | 0.1122          |
| 0.1131        | 0.95  | 4800  | 0.1119          |
| 0.1132        | 0.99  | 5000  | 0.1116          |
| 0.1132        | 1.03  | 5200  | 0.1115          |
| 0.1132        | 1.07  | 5400  | 0.1115          |
| 0.1123        | 1.11  | 5600  | 0.1112          |
| 0.1123        | 1.15  | 5800  | 0.1111          |
| 0.1116        | 1.19  | 6000  | 0.1110          |
| 0.1116        | 1.23  | 6200  | 0.1110          |
| 0.1116        | 1.27  | 6400  | 0.1108          |
| 0.1132        | 1.31  | 6600  | 0.1107          |
| 0.1132        | 1.35  | 6800  | 0.1122          |
| 0.2039        | 1.39  | 7000  | 0.1110          |
| 0.2039        | 1.43  | 7200  | 0.1108          |
| 0.2039        | 1.47  | 7400  | 0.1106          |
| 0.1107        | 1.51  | 7600  | 0.1106          |
| 0.1107        | 1.55  | 7800  | 0.1105          |
| 0.1115        | 1.59  | 8000  | 0.1104          |
| 0.1115        | 1.63  | 8200  | 0.1104          |
| 0.1115        | 1.67  | 8400  | 0.1104          |
| 0.1106        | 1.71  | 8600  | 0.1104          |
| 0.1106        | 1.75  | 8800  | 0.1103          |
| 0.1092        | 1.79  | 9000  | 0.1103          |
| 0.1092        | 1.83  | 9200  | 0.1103          |
| 0.1092        | 1.87  | 9400  | 0.1102          |
| 0.111         | 1.91  | 9600  | 0.1102          |
| 0.111         | 1.94  | 9800  | 0.1102          |
| 0.1109        | 1.98  | 10000 | 0.1102          |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.13.3