---
library_name: transformers
base_model: zhoudoe23/ChessQween3-base
tags:
- generated_from_trainer
model-index:
- name: ChessQween3-base-puzzled
  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-puzzled

This model is a fine-tuned version of [zhoudoe23/ChessQween3-base](https://huggingface.co/zhoudoe23/ChessQween3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8700

## 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: 3e-05
- 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 |
|:-------------:|:------:|:-----:|:---------------:|
| 1.1666        | 0.0233 | 1000  | 1.1704          |
| 1.0454        | 0.0466 | 2000  | 1.1195          |
| 1.1005        | 0.0700 | 3000  | 1.0880          |
| 1.0877        | 0.0933 | 4000  | 1.0663          |
| 1.0387        | 0.1166 | 5000  | 1.0488          |
| 1.1939        | 0.1399 | 6000  | 1.0355          |
| 1.1149        | 0.1633 | 7000  | 1.0199          |
| 1.0303        | 0.1866 | 8000  | 1.0077          |
| 1.0135        | 0.2099 | 9000  | 0.9969          |
| 1.0281        | 0.2332 | 10000 | 0.9883          |
| 0.9677        | 0.2566 | 11000 | 0.9776          |
| 1.0151        | 0.2799 | 12000 | 0.9704          |
| 0.9752        | 0.3032 | 13000 | 0.9628          |
| 0.9267        | 0.3265 | 14000 | 0.9540          |
| 1.0725        | 0.3499 | 15000 | 0.9486          |
| 1.0237        | 0.3732 | 16000 | 0.9456          |
| 0.9124        | 0.3965 | 17000 | 0.9355          |
| 0.8746        | 0.4198 | 18000 | 0.9291          |
| 1.0226        | 0.4431 | 19000 | 0.9235          |
| 0.8150        | 0.4665 | 20000 | 0.9190          |
| 0.9453        | 0.4898 | 21000 | 0.9152          |
| 0.8654        | 0.5131 | 22000 | 0.9089          |
| 1.0067        | 0.5364 | 23000 | 0.9057          |
| 0.8130        | 0.5598 | 24000 | 0.9016          |
| 0.9912        | 0.5831 | 25000 | 0.8974          |
| 0.8276        | 0.6064 | 26000 | 0.8950          |
| 0.9481        | 0.6297 | 27000 | 0.8912          |
| 0.9450        | 0.6531 | 28000 | 0.8884          |
| 0.8170        | 0.6764 | 29000 | 0.8853          |
| 0.9074        | 0.6997 | 30000 | 0.8833          |
| 0.9123        | 0.7230 | 31000 | 0.8817          |
| 0.8216        | 0.7464 | 32000 | 0.8783          |
| 0.8683        | 0.7697 | 33000 | 0.8765          |
| 0.8481        | 0.7930 | 34000 | 0.8748          |
| 0.8536        | 0.8163 | 35000 | 0.8735          |
| 0.7900        | 0.8397 | 36000 | 0.8729          |
| 0.8798        | 0.8630 | 37000 | 0.8718          |
| 0.8715        | 0.8863 | 38000 | 0.8712          |
| 0.8726        | 0.9096 | 39000 | 0.8705          |
| 0.8342        | 0.9329 | 40000 | 0.8702          |
| 0.8996        | 0.9563 | 41000 | 0.8700          |
| 0.8560        | 0.9796 | 42000 | 0.8700          |


### Framework versions

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