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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
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