File size: 3,810 Bytes
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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
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