amdchess-v9
This model is a fine-tuned version of amd/AMD-Llama-135m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6367
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use grokadamw with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.4763 | 0.0100 | 17 | 1.4222 |
1.0937 | 0.0201 | 34 | 1.1053 |
1.0732 | 0.0301 | 51 | 1.0270 |
0.991 | 0.0401 | 68 | 0.9671 |
1.0235 | 0.0502 | 85 | 0.9474 |
0.8849 | 0.0602 | 102 | 0.9239 |
0.9108 | 0.0702 | 119 | 0.8907 |
0.8907 | 0.0803 | 136 | 0.8745 |
0.8685 | 0.0903 | 153 | 0.8619 |
0.9375 | 0.1004 | 170 | 0.8547 |
0.7897 | 0.1104 | 187 | 0.8412 |
0.8594 | 0.1204 | 204 | 0.8293 |
0.8495 | 0.1305 | 221 | 0.8226 |
0.8618 | 0.1405 | 238 | 0.8129 |
0.8643 | 0.1505 | 255 | 0.8052 |
0.7375 | 0.1606 | 272 | 0.7985 |
0.7322 | 0.1706 | 289 | 0.7953 |
0.7991 | 0.1806 | 306 | 0.7923 |
0.8269 | 0.1907 | 323 | 0.7856 |
0.8031 | 0.2007 | 340 | 0.7776 |
0.7605 | 0.2107 | 357 | 0.7737 |
0.804 | 0.2208 | 374 | 0.7664 |
0.7683 | 0.2308 | 391 | 0.7600 |
0.7667 | 0.2409 | 408 | 0.7610 |
0.7823 | 0.2509 | 425 | 0.7508 |
0.7608 | 0.2609 | 442 | 0.7484 |
0.7291 | 0.2710 | 459 | 0.7457 |
0.8157 | 0.2810 | 476 | 0.7393 |
0.7526 | 0.2910 | 493 | 0.7353 |
0.7099 | 0.3011 | 510 | 0.7360 |
0.8242 | 0.3111 | 527 | 0.7331 |
0.7849 | 0.3211 | 544 | 0.7285 |
0.7558 | 0.3312 | 561 | 0.7224 |
0.6278 | 0.3412 | 578 | 0.7225 |
0.7135 | 0.3512 | 595 | 0.7197 |
0.6425 | 0.3613 | 612 | 0.7180 |
0.7721 | 0.3713 | 629 | 0.7137 |
0.8091 | 0.3813 | 646 | 0.7097 |
0.7518 | 0.3914 | 663 | 0.7063 |
0.7299 | 0.4014 | 680 | 0.7053 |
0.7563 | 0.4115 | 697 | 0.7051 |
0.658 | 0.4215 | 714 | 0.6997 |
0.7096 | 0.4315 | 731 | 0.6966 |
0.7555 | 0.4416 | 748 | 0.6954 |
0.7292 | 0.4516 | 765 | 0.6936 |
0.6349 | 0.4616 | 782 | 0.6908 |
0.6996 | 0.4717 | 799 | 0.6892 |
0.6849 | 0.4817 | 816 | 0.6892 |
0.7023 | 0.4917 | 833 | 0.6847 |
0.6547 | 0.5018 | 850 | 0.6850 |
0.7549 | 0.5118 | 867 | 0.6826 |
0.6987 | 0.5218 | 884 | 0.6798 |
0.648 | 0.5319 | 901 | 0.6796 |
0.7308 | 0.5419 | 918 | 0.6775 |
0.7245 | 0.5519 | 935 | 0.6756 |
0.6915 | 0.5620 | 952 | 0.6745 |
0.7287 | 0.5720 | 969 | 0.6716 |
0.739 | 0.5821 | 986 | 0.6704 |
0.7168 | 0.5921 | 1003 | 0.6686 |
0.685 | 0.6021 | 1020 | 0.6671 |
0.7183 | 0.6122 | 1037 | 0.6656 |
0.7138 | 0.6222 | 1054 | 0.6644 |
0.6738 | 0.6322 | 1071 | 0.6620 |
0.634 | 0.6423 | 1088 | 0.6611 |
0.703 | 0.6523 | 1105 | 0.6606 |
0.6538 | 0.6623 | 1122 | 0.6584 |
0.7167 | 0.6724 | 1139 | 0.6564 |
0.6717 | 0.6824 | 1156 | 0.6545 |
0.6633 | 0.6924 | 1173 | 0.6538 |
0.6035 | 0.7025 | 1190 | 0.6535 |
0.6444 | 0.7125 | 1207 | 0.6514 |
0.7171 | 0.7226 | 1224 | 0.6502 |
0.7157 | 0.7326 | 1241 | 0.6489 |
0.7028 | 0.7426 | 1258 | 0.6480 |
0.681 | 0.7527 | 1275 | 0.6479 |
0.6711 | 0.7627 | 1292 | 0.6464 |
0.7113 | 0.7727 | 1309 | 0.6454 |
0.7329 | 0.7828 | 1326 | 0.6454 |
0.694 | 0.7928 | 1343 | 0.6436 |
0.6304 | 0.8028 | 1360 | 0.6431 |
0.7129 | 0.8129 | 1377 | 0.6420 |
0.6531 | 0.8229 | 1394 | 0.6411 |
0.6791 | 0.8329 | 1411 | 0.6406 |
0.6963 | 0.8430 | 1428 | 0.6401 |
0.6285 | 0.8530 | 1445 | 0.6402 |
0.6484 | 0.8630 | 1462 | 0.6398 |
0.6505 | 0.8731 | 1479 | 0.6394 |
0.6985 | 0.8831 | 1496 | 0.6389 |
0.6643 | 0.8932 | 1513 | 0.6386 |
0.6292 | 0.9032 | 1530 | 0.6381 |
0.6237 | 0.9132 | 1547 | 0.6377 |
0.6159 | 0.9233 | 1564 | 0.6375 |
0.7027 | 0.9333 | 1581 | 0.6372 |
0.7068 | 0.9433 | 1598 | 0.6371 |
0.6021 | 0.9534 | 1615 | 0.6369 |
0.6812 | 0.9634 | 1632 | 0.6368 |
0.6805 | 0.9734 | 1649 | 0.6368 |
0.628 | 0.9835 | 1666 | 0.6367 |
0.6507 | 0.9935 | 1683 | 0.6367 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.1
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