--- license: gemma library_name: peft tags: - trl - sft - generated_from_trainer base_model: google/gemma-2b model-index: - name: gemma-2b-g results: [] --- # gemma-2b-g This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.9563 ## 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: 2.5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - training_steps: 500 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.016 | 2 | 0.9410 | | No log | 0.032 | 4 | 0.9443 | | No log | 0.048 | 6 | 0.9413 | | No log | 0.064 | 8 | 0.9398 | | No log | 0.08 | 10 | 0.9401 | | No log | 0.096 | 12 | 0.9406 | | No log | 0.112 | 14 | 0.9404 | | No log | 0.128 | 16 | 0.9409 | | No log | 0.144 | 18 | 0.9412 | | No log | 0.16 | 20 | 0.9412 | | No log | 0.176 | 22 | 0.9411 | | No log | 0.192 | 24 | 0.9408 | | No log | 0.208 | 26 | 0.9412 | | No log | 0.224 | 28 | 0.9411 | | No log | 0.24 | 30 | 0.9408 | | No log | 0.256 | 32 | 0.9406 | | No log | 0.272 | 34 | 0.9404 | | No log | 0.288 | 36 | 0.9406 | | No log | 0.304 | 38 | 0.9409 | | No log | 0.32 | 40 | 0.9414 | | No log | 0.336 | 42 | 0.9419 | | No log | 0.352 | 44 | 0.9425 | | No log | 0.368 | 46 | 0.9425 | | No log | 0.384 | 48 | 0.9416 | | No log | 0.4 | 50 | 0.9408 | | No log | 0.416 | 52 | 0.9403 | | No log | 0.432 | 54 | 0.9398 | | No log | 0.448 | 56 | 0.9393 | | No log | 0.464 | 58 | 0.9385 | | No log | 0.48 | 60 | 0.9390 | | No log | 0.496 | 62 | 0.9394 | | No log | 0.512 | 64 | 0.9392 | | No log | 0.528 | 66 | 0.9386 | | No log | 0.544 | 68 | 0.9385 | | No log | 0.56 | 70 | 0.9380 | | No log | 0.576 | 72 | 0.9373 | | No log | 0.592 | 74 | 0.9369 | | No log | 0.608 | 76 | 0.9367 | | No log | 0.624 | 78 | 0.9369 | | No log | 0.64 | 80 | 0.9370 | | No log | 0.656 | 82 | 0.9371 | | No log | 0.672 | 84 | 0.9366 | | No log | 0.688 | 86 | 0.9361 | | No log | 0.704 | 88 | 0.9361 | | No log | 0.72 | 90 | 0.9354 | | No log | 0.736 | 92 | 0.9352 | | No log | 0.752 | 94 | 0.9354 | | No log | 0.768 | 96 | 0.9352 | | No log | 0.784 | 98 | 0.9350 | | No log | 0.8 | 100 | 0.9349 | | No log | 0.816 | 102 | 0.9353 | | No log | 0.832 | 104 | 0.9349 | | No log | 0.848 | 106 | 0.9346 | | No log | 0.864 | 108 | 0.9341 | | No log | 0.88 | 110 | 0.9335 | | No log | 0.896 | 112 | 0.9327 | | No log | 0.912 | 114 | 0.9321 | | No log | 0.928 | 116 | 0.9323 | | No log | 0.944 | 118 | 0.9327 | | No log | 0.96 | 120 | 0.9325 | | No log | 0.976 | 122 | 0.9318 | | No log | 0.992 | 124 | 0.9316 | | No log | 1.008 | 126 | 0.9321 | | No log | 1.024 | 128 | 0.9332 | | No log | 1.04 | 130 | 0.9351 | | No log | 1.056 | 132 | 0.9370 | | No log | 1.072 | 134 | 0.9383 | | No log | 1.088 | 136 | 0.9390 | | No log | 1.104 | 138 | 0.9386 | | No log | 1.12 | 140 | 0.9378 | | No log | 1.1360 | 142 | 0.9375 | | No log | 1.152 | 144 | 0.9380 | | No log | 1.168 | 146 | 0.9380 | | No log | 1.184 | 148 | 0.9376 | | No log | 1.2 | 150 | 0.9381 | | No log | 1.216 | 152 | 0.9390 | | No log | 1.232 | 154 | 0.9400 | | No log | 1.248 | 156 | 0.9410 | | No log | 1.264 | 158 | 0.9411 | | No log | 1.28 | 160 | 0.9405 | | No log | 1.296 | 162 | 0.9402 | | No log | 1.312 | 164 | 0.9400 | | No log | 1.328 | 166 | 0.9399 | | No log | 1.3440 | 168 | 0.9397 | | No log | 1.3600 | 170 | 0.9398 | | No log | 1.376 | 172 | 0.9403 | | No log | 1.392 | 174 | 0.9412 | | No log | 1.408 | 176 | 0.9424 | | No log | 1.424 | 178 | 0.9432 | | No log | 1.44 | 180 | 0.9417 | | No log | 1.456 | 182 | 0.9403 | | No log | 1.472 | 184 | 0.9397 | | No log | 1.488 | 186 | 0.9393 | | No log | 1.504 | 188 | 0.9391 | | No log | 1.52 | 190 | 0.9385 | | No log | 1.536 | 192 | 0.9385 | | No log | 1.552 | 194 | 0.9387 | | No log | 1.568 | 196 | 0.9393 | | No log | 1.584 | 198 | 0.9402 | | No log | 1.6 | 200 | 0.9410 | | No log | 1.616 | 202 | 0.9410 | | No log | 1.6320 | 204 | 0.9417 | | No log | 1.6480 | 206 | 0.9414 | | No log | 1.6640 | 208 | 0.9410 | | No log | 1.6800 | 210 | 0.9402 | | No log | 1.696 | 212 | 0.9400 | | No log | 1.712 | 214 | 0.9398 | | No log | 1.728 | 216 | 0.9397 | | No log | 1.744 | 218 | 0.9395 | | No log | 1.76 | 220 | 0.9398 | | No log | 1.776 | 222 | 0.9400 | | No log | 1.792 | 224 | 0.9403 | | No log | 1.808 | 226 | 0.9403 | | No log | 1.8240 | 228 | 0.9399 | | No log | 1.8400 | 230 | 0.9392 | | No log | 1.8560 | 232 | 0.9385 | | No log | 1.8720 | 234 | 0.9385 | | No log | 1.888 | 236 | 0.9390 | | No log | 1.904 | 238 | 0.9394 | | No log | 1.92 | 240 | 0.9395 | | No log | 1.936 | 242 | 0.9392 | | No log | 1.952 | 244 | 0.9391 | | No log | 1.968 | 246 | 0.9390 | | No log | 1.984 | 248 | 0.9386 | | No log | 2.0 | 250 | 0.9380 | | No log | 2.016 | 252 | 0.9381 | | No log | 2.032 | 254 | 0.9401 | | No log | 2.048 | 256 | 0.9431 | | No log | 2.064 | 258 | 0.9469 | | No log | 2.08 | 260 | 0.9507 | | No log | 2.096 | 262 | 0.9529 | | No log | 2.112 | 264 | 0.9524 | | No log | 2.128 | 266 | 0.9501 | | No log | 2.144 | 268 | 0.9478 | | No log | 2.16 | 270 | 0.9466 | | No log | 2.176 | 272 | 0.9463 | | No log | 2.192 | 274 | 0.9458 | | No log | 2.208 | 276 | 0.9454 | | No log | 2.224 | 278 | 0.9451 | | No log | 2.24 | 280 | 0.9456 | | No log | 2.2560 | 282 | 0.9468 | | No log | 2.2720 | 284 | 0.9477 | | No log | 2.288 | 286 | 0.9484 | | No log | 2.304 | 288 | 0.9486 | | No log | 2.32 | 290 | 0.9479 | | No log | 2.336 | 292 | 0.9473 | | No log | 2.352 | 294 | 0.9473 | | No log | 2.368 | 296 | 0.9473 | | No log | 2.384 | 298 | 0.9475 | | No log | 2.4 | 300 | 0.9479 | | No log | 2.416 | 302 | 0.9490 | | No log | 2.432 | 304 | 0.9499 | | No log | 2.448 | 306 | 0.9501 | | No log | 2.464 | 308 | 0.9498 | | No log | 2.48 | 310 | 0.9491 | | No log | 2.496 | 312 | 0.9489 | | No log | 2.512 | 314 | 0.9490 | | No log | 2.528 | 316 | 0.9487 | | No log | 2.544 | 318 | 0.9483 | | No log | 2.56 | 320 | 0.9483 | | No log | 2.576 | 322 | 0.9483 | | No log | 2.592 | 324 | 0.9485 | | No log | 2.608 | 326 | 0.9487 | | No log | 2.624 | 328 | 0.9492 | | No log | 2.64 | 330 | 0.9493 | | No log | 2.656 | 332 | 0.9488 | | No log | 2.672 | 334 | 0.9487 | | No log | 2.6880 | 336 | 0.9486 | | No log | 2.7040 | 338 | 0.9485 | | No log | 2.7200 | 340 | 0.9481 | | No log | 2.7360 | 342 | 0.9477 | | No log | 2.752 | 344 | 0.9478 | | No log | 2.768 | 346 | 0.9482 | | No log | 2.784 | 348 | 0.9487 | | No log | 2.8 | 350 | 0.9483 | | No log | 2.816 | 352 | 0.9481 | | No log | 2.832 | 354 | 0.9480 | | No log | 2.848 | 356 | 0.9480 | | No log | 2.864 | 358 | 0.9479 | | No log | 2.88 | 360 | 0.9481 | | No log | 2.896 | 362 | 0.9484 | | No log | 2.912 | 364 | 0.9488 | | No log | 2.928 | 366 | 0.9490 | | No log | 2.944 | 368 | 0.9489 | | No log | 2.96 | 370 | 0.9487 | | No log | 2.976 | 372 | 0.9484 | | No log | 2.992 | 374 | 0.9476 | | No log | 3.008 | 376 | 0.9468 | | No log | 3.024 | 378 | 0.9471 | | No log | 3.04 | 380 | 0.9481 | | No log | 3.056 | 382 | 0.9499 | | No log | 3.072 | 384 | 0.9521 | | No log | 3.088 | 386 | 0.9543 | | No log | 3.104 | 388 | 0.9562 | | No log | 3.12 | 390 | 0.9572 | | No log | 3.136 | 392 | 0.9577 | | No log | 3.152 | 394 | 0.9577 | | No log | 3.168 | 396 | 0.9577 | | No log | 3.184 | 398 | 0.9574 | | No log | 3.2 | 400 | 0.9570 | | No log | 3.216 | 402 | 0.9569 | | No log | 3.232 | 404 | 0.9567 | | No log | 3.248 | 406 | 0.9565 | | No log | 3.2640 | 408 | 0.9564 | | No log | 3.2800 | 410 | 0.9562 | | No log | 3.296 | 412 | 0.9561 | | No log | 3.312 | 414 | 0.9561 | | No log | 3.328 | 416 | 0.9562 | | No log | 3.344 | 418 | 0.9565 | | No log | 3.36 | 420 | 0.9568 | | No log | 3.376 | 422 | 0.9570 | | No log | 3.392 | 424 | 0.9572 | | No log | 3.408 | 426 | 0.9573 | | No log | 3.424 | 428 | 0.9572 | | No log | 3.44 | 430 | 0.9569 | | No log | 3.456 | 432 | 0.9570 | | No log | 3.472 | 434 | 0.9572 | | No log | 3.488 | 436 | 0.9574 | | No log | 3.504 | 438 | 0.9575 | | No log | 3.52 | 440 | 0.9577 | | No log | 3.536 | 442 | 0.9577 | | No log | 3.552 | 444 | 0.9578 | | No log | 3.568 | 446 | 0.9579 | | No log | 3.584 | 448 | 0.9577 | | No log | 3.6 | 450 | 0.9575 | | No log | 3.616 | 452 | 0.9575 | | No log | 3.632 | 454 | 0.9575 | | No log | 3.648 | 456 | 0.9576 | | No log | 3.664 | 458 | 0.9576 | | No log | 3.68 | 460 | 0.9574 | | No log | 3.6960 | 462 | 0.9573 | | No log | 3.7120 | 464 | 0.9571 | | No log | 3.7280 | 466 | 0.9569 | | No log | 3.7440 | 468 | 0.9567 | | No log | 3.76 | 470 | 0.9565 | | No log | 3.776 | 472 | 0.9563 | | No log | 3.792 | 474 | 0.9563 | | No log | 3.808 | 476 | 0.9563 | | No log | 3.824 | 478 | 0.9564 | | No log | 3.84 | 480 | 0.9565 | | No log | 3.856 | 482 | 0.9565 | | No log | 3.872 | 484 | 0.9566 | | No log | 3.888 | 486 | 0.9566 | | No log | 3.904 | 488 | 0.9565 | | No log | 3.92 | 490 | 0.9565 | | No log | 3.936 | 492 | 0.9565 | | No log | 3.952 | 494 | 0.9564 | | No log | 3.968 | 496 | 0.9564 | | No log | 3.984 | 498 | 0.9564 | | 0.814 | 4.0 | 500 | 0.9563 | ### Framework versions - PEFT 0.10.1.dev0 - Transformers 4.40.0.dev0 - Pytorch 2.2.2+cu121 - Datasets 2.18.0 - Tokenizers 0.19.1