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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: PleIAs/Monad |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: monad-chess |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# monad-chess |
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This model is a fine-tuned version of [PleIAs/Monad](https://huggingface.co/PleIAs/Monad) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8021 |
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- Accuracy: 0.0 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| 1.0912 | 0.1616 | 200 | 1.0668 | 0.0001 | |
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| 1.0167 | 0.3231 | 400 | 0.9883 | 0.0 | |
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| 0.9614 | 0.4847 | 600 | 0.9587 | 0.0 | |
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| 0.926 | 0.6462 | 800 | 0.9231 | 0.0 | |
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| 0.9032 | 0.8078 | 1000 | 0.8942 | 0.0 | |
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| 0.8828 | 0.9693 | 1200 | 0.8803 | 0.0 | |
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| 0.8739 | 1.1309 | 1400 | 0.8659 | 0.0 | |
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| 0.844 | 1.2924 | 1600 | 0.8526 | 0.0 | |
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| 0.8531 | 1.4540 | 1800 | 0.8453 | 0.0 | |
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| 0.8254 | 1.6155 | 2000 | 0.8297 | 0.0 | |
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| 0.8434 | 1.7771 | 2200 | 0.8263 | 0.0 | |
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| 0.8217 | 1.9386 | 2400 | 0.8189 | 0.0 | |
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| 0.8034 | 2.1002 | 2600 | 0.8121 | 0.0 | |
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| 0.8051 | 2.2617 | 2800 | 0.8082 | 0.0 | |
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| 0.7945 | 2.4233 | 3000 | 0.8062 | 0.0 | |
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| 0.7975 | 2.5848 | 3200 | 0.8040 | 0.0 | |
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| 0.7881 | 2.7464 | 3400 | 0.8026 | 0.0 | |
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| 0.7951 | 2.9079 | 3600 | 0.8021 | 0.0 | |
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### Framework versions |
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- Transformers 4.57.2 |
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- Pytorch 2.9.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.1 |
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