---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: ChessQween3-base
  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. -->

# ChessQween3-base

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9453

## 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: 128
- eval_batch_size: 64
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 512
- total_eval_batch_size: 128
- 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
- lr_scheduler_warmup_steps: 1000
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 3.7947        | 0.0256 | 2000  | 3.7973          |
| 3.2355        | 0.0512 | 4000  | 3.3104          |
| 3.1324        | 0.0768 | 6000  | 3.0861          |
| 3.0801        | 0.1025 | 8000  | 2.9574          |
| 2.9370        | 0.1281 | 10000 | 2.8806          |
| 2.8139        | 0.1537 | 12000 | 2.7924          |
| 2.7011        | 0.1793 | 14000 | 2.7364          |
| 2.5453        | 0.2049 | 16000 | 2.6827          |
| 2.6728        | 0.2305 | 18000 | 2.6320          |
| 2.5903        | 0.2561 | 20000 | 2.5825          |
| 2.5910        | 0.2817 | 22000 | 2.5478          |
| 2.4977        | 0.3074 | 24000 | 2.5110          |
| 2.5118        | 0.3330 | 26000 | 2.4747          |
| 2.4336        | 0.3586 | 28000 | 2.4338          |
| 2.4289        | 0.3842 | 30000 | 2.3929          |
| 2.3808        | 0.4098 | 32000 | 2.3621          |
| 2.3663        | 0.4354 | 34000 | 2.3340          |
| 2.3412        | 0.4610 | 36000 | 2.3026          |
| 2.3884        | 0.4866 | 38000 | 2.2735          |
| 2.3094        | 0.5123 | 40000 | 2.2408          |
| 2.3330        | 0.5379 | 42000 | 2.2155          |
| 2.1700        | 0.5635 | 44000 | 2.1895          |
| 2.1146        | 0.5891 | 46000 | 2.1646          |
| 2.1595        | 0.6147 | 48000 | 2.1398          |
| 2.0966        | 0.6403 | 50000 | 2.1140          |
| 2.2037        | 0.6659 | 52000 | 2.0877          |
| 1.9864        | 0.6915 | 54000 | 2.0719          |
| 2.0506        | 0.7172 | 56000 | 2.0551          |
| 1.9694        | 0.7428 | 58000 | 2.0328          |
| 2.1410        | 0.7684 | 60000 | 2.0160          |
| 2.0000        | 0.7940 | 62000 | 1.9990          |
| 1.9383        | 0.8196 | 64000 | 1.9859          |
| 2.0483        | 0.8452 | 66000 | 1.9706          |
| 1.9896        | 0.8708 | 68000 | 1.9616          |
| 1.9138        | 0.8965 | 70000 | 1.9552          |
| 2.0671        | 0.9221 | 72000 | 1.9515          |
| 1.9800        | 0.9477 | 74000 | 1.9467          |
| 1.9927        | 0.9733 | 76000 | 1.9455          |
| 1.9911        | 0.9989 | 78000 | 1.9453          |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2