---
library_name: transformers
license: mit
base_model: microsoft/DialoGPT-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: dialochess-v3
  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. -->

# dialochess-v3

This model is a fine-tuned version of [microsoft/DialoGPT-small](https://huggingface.co/microsoft/DialoGPT-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8843
- Accuracy: 0.0002

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.3128        | 0.1616 | 200  | 1.1914          | 0.0002   |
| 1.1935        | 0.3231 | 400  | 1.0974          | 0.0002   |
| 1.1181        | 0.4847 | 600  | 1.0419          | 0.0      |
| 1.0778        | 0.6462 | 800  | 1.0080          | 0.0      |
| 1.0426        | 0.8078 | 1000 | 0.9828          | 0.0002   |
| 1.0185        | 0.9693 | 1200 | 0.9612          | 0.0002   |
| 1.0075        | 1.1309 | 1400 | 0.9458          | 0.0001   |
| 0.9765        | 1.2924 | 1600 | 0.9348          | 0.0002   |
| 0.9806        | 1.4540 | 1800 | 0.9248          | 0.0001   |
| 0.9542        | 1.6155 | 2000 | 0.9132          | 0.0002   |
| 0.9684        | 1.7771 | 2200 | 0.9059          | 0.0002   |
| 0.9525        | 1.9386 | 2400 | 0.9015          | 0.0002   |
| 0.9396        | 2.1002 | 2600 | 0.8960          | 0.0002   |
| 0.9342        | 2.2617 | 2800 | 0.8896          | 0.0002   |
| 0.9327        | 2.4233 | 3000 | 0.8874          | 0.0002   |
| 0.9344        | 2.5848 | 3200 | 0.8848          | 0.0002   |
| 0.9272        | 2.7464 | 3400 | 0.8848          | 0.0002   |
| 0.9288        | 2.9079 | 3600 | 0.8843          | 0.0002   |


### Framework versions

- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1