--- library_name: peft license: apache-2.0 base_model: Qwen/Qwen2-VL-7B-Instruct tags: - trl - sft - generated_from_trainer model-index: - name: qwen2-7b-instruct-trl-sft-ChartQA results: [] --- # qwen2-7b-instruct-trl-sft-ChartQA This model is a fine-tuned version of [Qwen/Qwen2-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.2465 ## 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: 0.0002 - train_batch_size: 1 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 8 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: constant - lr_scheduler_warmup_ratio: 0.03 - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 2.6558 | 0.0283 | 10 | 2.1357 | | 1.6719 | 0.0565 | 20 | 1.0837 | | 0.7281 | 0.0848 | 30 | 0.4616 | | 0.4803 | 0.1131 | 40 | 0.4224 | | 0.4368 | 0.1413 | 50 | 0.3542 | | 0.3313 | 0.1696 | 60 | 0.3046 | | 0.317 | 0.1979 | 70 | 0.2986 | | 0.3106 | 0.2261 | 80 | 0.2907 | | 0.3115 | 0.2544 | 90 | 0.2879 | | 0.3236 | 0.2827 | 100 | 0.2806 | | 0.2803 | 0.3110 | 110 | 0.2726 | | 0.3057 | 0.3392 | 120 | 0.2768 | | 0.2897 | 0.3675 | 130 | 0.2780 | | 0.2772 | 0.3958 | 140 | 0.2755 | | 0.312 | 0.4240 | 150 | 0.2696 | | 0.2554 | 0.4523 | 160 | 0.2674 | | 0.2885 | 0.4806 | 170 | 0.2714 | | 0.2831 | 0.5088 | 180 | 0.2699 | | 0.2689 | 0.5371 | 190 | 0.2616 | | 0.2819 | 0.5654 | 200 | 0.2607 | | 0.2818 | 0.5936 | 210 | 0.2673 | | 0.2931 | 0.6219 | 220 | 0.2595 | | 0.2604 | 0.6502 | 230 | 0.2594 | | 0.3043 | 0.6784 | 240 | 0.2561 | | 0.2815 | 0.7067 | 250 | 0.2547 | | 0.2914 | 0.7350 | 260 | 0.2552 | | 0.2523 | 0.7633 | 270 | 0.2534 | | 0.2589 | 0.7915 | 280 | 0.2540 | | 0.2654 | 0.8198 | 290 | 0.2519 | | 0.2917 | 0.8481 | 300 | 0.2490 | | 0.2759 | 0.8763 | 310 | 0.2498 | | 0.2766 | 0.9046 | 320 | 0.2474 | | 0.2502 | 0.9329 | 330 | 0.2476 | | 0.2738 | 0.9611 | 340 | 0.2462 | | 0.2806 | 0.9894 | 350 | 0.2453 | | 0.2648 | 1.0177 | 360 | 0.2465 | | 0.2659 | 1.0459 | 370 | 0.2448 | | 0.247 | 1.0742 | 380 | 0.2450 | | 0.2692 | 1.1025 | 390 | 0.2488 | | 0.2565 | 1.1307 | 400 | 0.2483 | | 0.2264 | 1.1590 | 410 | 0.2470 | | 0.2647 | 1.1873 | 420 | 0.2461 | | 0.2438 | 1.2155 | 430 | 0.2485 | | 0.2421 | 1.2438 | 440 | 0.2448 | | 0.2693 | 1.2721 | 450 | 0.2432 | | 0.262 | 1.3004 | 460 | 0.2426 | | 0.2659 | 1.3286 | 470 | 0.2437 | | 0.2375 | 1.3569 | 480 | 0.2479 | | 0.2312 | 1.3852 | 490 | 0.2523 | | 0.2503 | 1.4134 | 500 | 0.2511 | | 0.2377 | 1.4417 | 510 | 0.2464 | | 0.2385 | 1.4700 | 520 | 0.2432 | | 0.2462 | 1.4982 | 530 | 0.2436 | | 0.2462 | 1.5265 | 540 | 0.2464 | | 0.2766 | 1.5548 | 550 | 0.2488 | | 0.2407 | 1.5830 | 560 | 0.2474 | | 0.2505 | 1.6113 | 570 | 0.2442 | | 0.2291 | 1.6396 | 580 | 0.2456 | | 0.244 | 1.6678 | 590 | 0.2444 | | 0.2355 | 1.6961 | 600 | 0.2446 | | 0.2458 | 1.7244 | 610 | 0.2452 | | 0.2478 | 1.7527 | 620 | 0.2451 | | 0.2687 | 1.7809 | 630 | 0.2450 | | 0.2397 | 1.8092 | 640 | 0.2478 | | 0.2436 | 1.8375 | 650 | 0.2478 | | 0.2293 | 1.8657 | 660 | 0.2489 | | 0.2341 | 1.8940 | 670 | 0.2476 | | 0.2252 | 1.9223 | 680 | 0.2476 | | 0.2505 | 1.9505 | 690 | 0.2522 | | 0.2647 | 1.9788 | 700 | 0.2517 | | 0.2428 | 2.0071 | 710 | 0.2495 | | 0.2261 | 2.0353 | 720 | 0.2476 | | 0.2466 | 2.0636 | 730 | 0.2460 | | 0.222 | 2.0919 | 740 | 0.2453 | | 0.2382 | 2.1201 | 750 | 0.2460 | | 0.2122 | 2.1484 | 760 | 0.2473 | | 0.2202 | 2.1767 | 770 | 0.2517 | | 0.2157 | 2.2049 | 780 | 0.2495 | | 0.2425 | 2.2332 | 790 | 0.2474 | | 0.2547 | 2.2615 | 800 | 0.2477 | | 0.2425 | 2.2898 | 810 | 0.2488 | | 0.2337 | 2.3180 | 820 | 0.2497 | | 0.2201 | 2.3463 | 830 | 0.2487 | | 0.2251 | 2.3746 | 840 | 0.2467 | | 0.2028 | 2.4028 | 850 | 0.2463 | | 0.2221 | 2.4311 | 860 | 0.2480 | | 0.2193 | 2.4594 | 870 | 0.2517 | | 0.2076 | 2.4876 | 880 | 0.2595 | | 0.2201 | 2.5159 | 890 | 0.2552 | | 0.2303 | 2.5442 | 900 | 0.2536 | | 0.2156 | 2.5724 | 910 | 0.2509 | | 0.216 | 2.6007 | 920 | 0.2501 | | 0.2084 | 2.6290 | 930 | 0.2516 | | 0.2157 | 2.6572 | 940 | 0.2448 | | 0.2214 | 2.6855 | 950 | 0.2450 | | 0.2237 | 2.7138 | 960 | 0.2456 | | 0.2041 | 2.7420 | 970 | 0.2501 | | 0.1986 | 2.7703 | 980 | 0.2537 | | 0.2238 | 2.7986 | 990 | 0.2531 | | 0.2178 | 2.8269 | 1000 | 0.2512 | | 0.2172 | 2.8551 | 1010 | 0.2477 | | 0.2221 | 2.8834 | 1020 | 0.2554 | | 0.2212 | 2.9117 | 1030 | 0.2497 | | 0.2039 | 2.9399 | 1040 | 0.2478 | | 0.2266 | 2.9682 | 1050 | 0.2465 | ### Framework versions - PEFT 0.13.0 - Transformers 4.45.1 - Pytorch 2.4.0+cu121 - Datasets 3.0.1 - Tokenizers 0.20.1