---
library_name: transformers
license: apache-2.0
base_model: PleIAs/Monad
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: monad-chess
  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. -->

# monad-chess

This model is a fine-tuned version of [PleIAs/Monad](https://huggingface.co/PleIAs/Monad) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8021
- Accuracy: 0.0

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.0912        | 0.1616 | 200  | 1.0668          | 0.0001   |
| 1.0167        | 0.3231 | 400  | 0.9883          | 0.0      |
| 0.9614        | 0.4847 | 600  | 0.9587          | 0.0      |
| 0.926         | 0.6462 | 800  | 0.9231          | 0.0      |
| 0.9032        | 0.8078 | 1000 | 0.8942          | 0.0      |
| 0.8828        | 0.9693 | 1200 | 0.8803          | 0.0      |
| 0.8739        | 1.1309 | 1400 | 0.8659          | 0.0      |
| 0.844         | 1.2924 | 1600 | 0.8526          | 0.0      |
| 0.8531        | 1.4540 | 1800 | 0.8453          | 0.0      |
| 0.8254        | 1.6155 | 2000 | 0.8297          | 0.0      |
| 0.8434        | 1.7771 | 2200 | 0.8263          | 0.0      |
| 0.8217        | 1.9386 | 2400 | 0.8189          | 0.0      |
| 0.8034        | 2.1002 | 2600 | 0.8121          | 0.0      |
| 0.8051        | 2.2617 | 2800 | 0.8082          | 0.0      |
| 0.7945        | 2.4233 | 3000 | 0.8062          | 0.0      |
| 0.7975        | 2.5848 | 3200 | 0.8040          | 0.0      |
| 0.7881        | 2.7464 | 3400 | 0.8026          | 0.0      |
| 0.7951        | 2.9079 | 3600 | 0.8021          | 0.0      |


### Framework versions

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