---
library_name: transformers
license: mit
base_model: gpt2-medium
tags:
- generated_from_trainer
model-index:
- name: chessgpt2-medium-m
  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. -->

# chessgpt2-medium-m

This model is a fine-tuned version of [gpt2-medium](https://huggingface.co/gpt2-medium) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9654

## 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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.025
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 2.4607        | 0.1280 | 1000  | 1.8105          |
| 1.6726        | 0.2560 | 2000  | 1.4939          |
| 1.4686        | 0.3839 | 3000  | 1.3617          |
| 1.3601        | 0.5119 | 4000  | 1.2698          |
| 1.2875        | 0.6399 | 5000  | 1.2164          |
| 1.2366        | 0.7679 | 6000  | 1.1717          |
| 1.1992        | 0.8958 | 7000  | 1.1404          |
| 1.1646        | 1.0238 | 8000  | 1.1097          |
| 1.126         | 1.1518 | 9000  | 1.0934          |
| 1.1085        | 1.2798 | 10000 | 1.0705          |
| 1.0875        | 1.4077 | 11000 | 1.0541          |
| 1.0733        | 1.5357 | 12000 | 1.0388          |
| 1.059         | 1.6637 | 13000 | 1.0246          |
| 1.0451        | 1.7917 | 14000 | 1.0109          |
| 1.0327        | 1.9196 | 15000 | 1.0018          |
| 1.0118        | 2.0476 | 16000 | 0.9915          |
| 0.9862        | 2.1756 | 17000 | 0.9861          |
| 0.9806        | 2.3036 | 18000 | 0.9783          |
| 0.9757        | 2.4315 | 19000 | 0.9736          |
| 0.9713        | 2.5595 | 20000 | 0.9695          |
| 0.9675        | 2.6875 | 21000 | 0.9671          |
| 0.9659        | 2.8155 | 22000 | 0.9658          |
| 0.965         | 2.9434 | 23000 | 0.9654          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1