--- library_name: transformers license: apache-2.0 base_model: reflex-ai/AMD-Llama-350M-Upgraded tags: - generated_from_trainer model-index: - name: amdchess results: [] --- # amdchess This model is a fine-tuned version of [reflex-ai/AMD-Llama-350M-Upgraded](https://huggingface.co/reflex-ai/AMD-Llama-350M-Upgraded) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.6347 ## 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: 4 - eval_batch_size: 4 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - num_epochs: 0.1 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 8.019 | 0.0012 | 4 | 7.6135 | | 7.7094 | 0.0024 | 8 | 7.0826 | | 6.8737 | 0.0035 | 12 | 6.8392 | | 6.6426 | 0.0047 | 16 | 6.6142 | | 6.3563 | 0.0059 | 20 | 6.2879 | | 6.0826 | 0.0071 | 24 | 5.9688 | | 5.8464 | 0.0083 | 28 | 5.5885 | | 5.3209 | 0.0094 | 32 | 5.4342 | | 5.2345 | 0.0106 | 36 | 5.2125 | | 4.9003 | 0.0118 | 40 | 4.9282 | | 4.6779 | 0.0130 | 44 | 4.7029 | | 4.3778 | 0.0142 | 48 | 4.3920 | | 4.3256 | 0.0154 | 52 | 4.1814 | | 3.9975 | 0.0165 | 56 | 4.0072 | | 3.73 | 0.0177 | 60 | 3.8358 | | 4.0483 | 0.0189 | 64 | 3.7093 | | 3.7907 | 0.0201 | 68 | 3.5874 | | 3.3881 | 0.0213 | 72 | 3.4606 | | 3.5066 | 0.0224 | 76 | 3.4071 | | 3.3845 | 0.0236 | 80 | 3.2889 | | 3.2318 | 0.0248 | 84 | 3.1932 | | 3.5897 | 0.0260 | 88 | 3.1209 | | 3.0362 | 0.0272 | 92 | 3.0123 | | 2.7973 | 0.0283 | 96 | 2.9055 | | 2.8976 | 0.0295 | 100 | 2.8210 | | 2.8188 | 0.0307 | 104 | 2.7422 | | 2.5149 | 0.0319 | 108 | 2.6395 | | 2.495 | 0.0331 | 112 | 2.5714 | | 2.5654 | 0.0342 | 116 | 2.4863 | | 2.4205 | 0.0354 | 120 | 2.4448 | | 2.3487 | 0.0366 | 124 | 2.3561 | | 2.413 | 0.0378 | 128 | 2.3265 | | 2.2713 | 0.0390 | 132 | 2.2814 | | 2.2293 | 0.0402 | 136 | 2.2361 | | 2.2793 | 0.0413 | 140 | 2.1745 | | 2.185 | 0.0425 | 144 | 2.1444 | | 2.0137 | 0.0437 | 148 | 2.1245 | | 2.1408 | 0.0449 | 152 | 2.0849 | | 2.1539 | 0.0461 | 156 | 2.0650 | | 2.0592 | 0.0472 | 160 | 2.0345 | | 1.9849 | 0.0484 | 164 | 2.0390 | | 1.8796 | 0.0496 | 168 | 1.9978 | | 1.9646 | 0.0508 | 172 | 1.9860 | | 1.9913 | 0.0520 | 176 | 1.9388 | | 1.967 | 0.0531 | 180 | 1.9121 | | 1.9141 | 0.0543 | 184 | 1.9085 | | 1.9513 | 0.0555 | 188 | 1.9040 | | 1.9123 | 0.0567 | 192 | 1.8606 | | 1.8204 | 0.0579 | 196 | 1.8556 | | 1.9311 | 0.0590 | 200 | 1.8390 | | 1.8425 | 0.0602 | 204 | 1.8162 | | 1.7932 | 0.0614 | 208 | 1.7914 | | 1.591 | 0.0626 | 212 | 1.7749 | | 1.7899 | 0.0638 | 216 | 1.7667 | | 1.7094 | 0.0650 | 220 | 1.7637 | | 1.8023 | 0.0661 | 224 | 1.7458 | | 1.7368 | 0.0673 | 228 | 1.7339 | | 1.5679 | 0.0685 | 232 | 1.7281 | | 1.7265 | 0.0697 | 236 | 1.7221 | | 1.7034 | 0.0709 | 240 | 1.7093 | | 1.5902 | 0.0720 | 244 | 1.7086 | | 1.6903 | 0.0732 | 248 | 1.6976 | | 1.7581 | 0.0744 | 252 | 1.6944 | | 1.656 | 0.0756 | 256 | 1.6899 | | 1.4287 | 0.0768 | 260 | 1.6858 | | 1.6527 | 0.0779 | 264 | 1.6754 | | 1.7206 | 0.0791 | 268 | 1.6787 | | 1.8268 | 0.0803 | 272 | 1.6673 | | 1.538 | 0.0815 | 276 | 1.6590 | | 1.7374 | 0.0827 | 280 | 1.6711 | | 1.7255 | 0.0839 | 284 | 1.6513 | | 1.6032 | 0.0850 | 288 | 1.6552 | | 1.5297 | 0.0862 | 292 | 1.6458 | | 1.7639 | 0.0874 | 296 | 1.6488 | | 1.8029 | 0.0886 | 300 | 1.6441 | | 1.665 | 0.0898 | 304 | 1.6425 | | 1.6854 | 0.0909 | 308 | 1.6425 | | 1.5418 | 0.0921 | 312 | 1.6396 | | 1.6943 | 0.0933 | 316 | 1.6373 | | 1.6758 | 0.0945 | 320 | 1.6359 | | 1.9994 | 0.0957 | 324 | 1.6352 | | 1.6326 | 0.0968 | 328 | 1.6349 | | 1.6935 | 0.0980 | 332 | 1.6348 | | 1.6358 | 0.0992 | 336 | 1.6347 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.5.0+cu121 - Datasets 3.0.2 - Tokenizers 0.19.1