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

# chessgpt-medium-l

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: 0.7634

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.4326        | 0.064 | 1000  | 1.3596          |
| 1.2424        | 0.128 | 2000  | 1.1829          |
| 1.1278        | 0.192 | 3000  | 1.0753          |
| 1.0296        | 0.256 | 4000  | 0.9877          |
| 0.9605        | 0.32  | 5000  | 0.9224          |
| 0.9193        | 0.384 | 6000  | 0.8874          |
| 0.8911        | 0.448 | 7000  | 0.8600          |
| 0.8707        | 0.512 | 8000  | 0.8405          |
| 0.8521        | 0.576 | 9000  | 0.8221          |
| 0.8391        | 0.64  | 10000 | 0.8089          |
| 0.8242        | 0.704 | 11000 | 0.7972          |
| 0.8146        | 0.768 | 12000 | 0.7858          |
| 0.8047        | 0.832 | 13000 | 0.7769          |
| 0.7974        | 0.896 | 14000 | 0.7701          |
| 0.7916        | 0.96  | 15000 | 0.7651          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1