---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: gpt2-p10k
  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-p10k

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: 0.0241

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| No log        | 0.2   | 200   | 0.0558          |
| No log        | 0.4   | 400   | 0.1944          |
| 0.2826        | 0.6   | 600   | 0.3970          |
| 0.2826        | 0.8   | 800   | 0.6245          |
| 0.8928        | 1.0   | 1000  | 2.0545          |
| 0.8928        | 1.2   | 1200  | 0.3789          |
| 0.8928        | 1.4   | 1400  | 0.4120          |
| 0.5735        | 1.6   | 1600  | 0.9738          |
| 0.5735        | 1.8   | 1800  | 1.4284          |
| 3.2584        | 2.0   | 2000  | 3.8628          |
| 3.2584        | 2.2   | 2200  | 0.6803          |
| 3.2584        | 2.4   | 2400  | 0.4168          |
| 1.1454        | 2.6   | 2600  | 0.0628          |
| 1.1454        | 2.8   | 2800  | 0.0353          |
| 0.0693        | 3.0   | 3000  | 0.0301          |
| 0.0693        | 3.2   | 3200  | 0.0294          |
| 0.0693        | 3.4   | 3400  | 0.0284          |
| 0.0299        | 3.6   | 3600  | 0.0279          |
| 0.0299        | 3.8   | 3800  | 0.0274          |
| 0.0287        | 4.0   | 4000  | 0.0274          |
| 0.0287        | 4.2   | 4200  | 0.0271          |
| 0.0287        | 4.4   | 4400  | 0.0260          |
| 0.0274        | 4.6   | 4600  | 0.0260          |
| 0.0274        | 4.8   | 4800  | 0.0261          |
| 0.0267        | 5.0   | 5000  | 0.0257          |
| 0.0267        | 5.2   | 5200  | 0.0255          |
| 0.0267        | 5.4   | 5400  | 0.0255          |
| 0.0263        | 5.6   | 5600  | 0.0254          |
| 0.0263        | 5.8   | 5800  | 0.0250          |
| 0.0259        | 6.0   | 6000  | 0.0250          |
| 0.0259        | 6.2   | 6200  | 0.0252          |
| 0.0259        | 6.4   | 6400  | 0.0253          |
| 0.0256        | 6.6   | 6600  | 0.0250          |
| 0.0256        | 6.8   | 6800  | 0.0247          |
| 0.0253        | 7.0   | 7000  | 0.0256          |
| 0.0253        | 7.2   | 7200  | 0.0247          |
| 0.0253        | 7.4   | 7400  | 0.0245          |
| 0.0251        | 7.6   | 7600  | 0.0245          |
| 0.0251        | 7.8   | 7800  | 0.0245          |
| 0.0251        | 8.0   | 8000  | 0.0246          |
| 0.0251        | 8.2   | 8200  | 0.0244          |
| 0.0251        | 8.4   | 8400  | 0.0246          |
| 0.0252        | 8.6   | 8600  | 0.0243          |
| 0.0252        | 8.8   | 8800  | 0.0242          |
| 0.0244        | 9.0   | 9000  | 0.0242          |
| 0.0244        | 9.2   | 9200  | 0.0242          |
| 0.0244        | 9.4   | 9400  | 0.0242          |
| 0.0247        | 9.6   | 9600  | 0.0242          |
| 0.0247        | 9.8   | 9800  | 0.0241          |
| 0.0245        | 10.0  | 10000 | 0.0241          |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1