--- license: apache-2.0 library_name: peft tags: - trl - sft - generated_from_trainer base_model: mistralai/Mixtral-8x7B-v0.1 model-index: - name: results_mixtral_sft results: [] --- # results_mixtral_sft This model is a fine-tuned version of [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2331 ## 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: 2e-05 - train_batch_size: 10 - eval_batch_size: 10 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 20 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 25 - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | No log | 1.0 | 1 | 2.4533 | | No log | 2.0 | 2 | 2.4493 | | No log | 3.0 | 3 | 2.4436 | | No log | 4.0 | 4 | 2.4352 | | No log | 5.0 | 5 | 2.4249 | | No log | 6.0 | 6 | 2.4215 | | No log | 7.0 | 7 | 2.4047 | | No log | 8.0 | 8 | 2.3842 | | No log | 9.0 | 9 | 2.3561 | | No log | 10.0 | 10 | 2.3295 | | No log | 11.0 | 11 | 2.3004 | | No log | 12.0 | 12 | 2.2563 | | No log | 13.0 | 13 | 2.2130 | | No log | 14.0 | 14 | 2.1715 | | No log | 15.0 | 15 | 2.1203 | | No log | 16.0 | 16 | 2.0893 | | No log | 17.0 | 17 | 2.0458 | | No log | 18.0 | 18 | 1.9937 | | No log | 19.0 | 19 | 1.9469 | | No log | 20.0 | 20 | 1.9085 | | No log | 21.0 | 21 | 1.9413 | | No log | 22.0 | 22 | 1.8690 | | No log | 23.0 | 23 | 1.8139 | | No log | 24.0 | 24 | 1.7389 | | 1.0996 | 25.0 | 25 | 1.6836 | | 1.0996 | 26.0 | 26 | 1.6236 | | 1.0996 | 27.0 | 27 | 1.5705 | | 1.0996 | 28.0 | 28 | 1.5261 | | 1.0996 | 29.0 | 29 | 1.4790 | | 1.0996 | 30.0 | 30 | 1.4240 | | 1.0996 | 31.0 | 31 | 1.3674 | | 1.0996 | 32.0 | 32 | 1.3182 | | 1.0996 | 33.0 | 33 | 1.2769 | | 1.0996 | 34.0 | 34 | 1.2321 | | 1.0996 | 35.0 | 35 | 1.1885 | | 1.0996 | 36.0 | 36 | 1.1445 | | 1.0996 | 37.0 | 37 | 1.0878 | | 1.0996 | 38.0 | 38 | 1.0237 | | 1.0996 | 39.0 | 39 | 0.9748 | | 1.0996 | 40.0 | 40 | 0.9294 | | 1.0996 | 41.0 | 41 | 0.8806 | | 1.0996 | 42.0 | 42 | 0.8457 | | 1.0996 | 43.0 | 43 | 0.7969 | | 1.0996 | 44.0 | 44 | 0.7599 | | 1.0996 | 45.0 | 45 | 0.7189 | | 1.0996 | 46.0 | 46 | 0.6952 | | 1.0996 | 47.0 | 47 | 0.6570 | | 1.0996 | 48.0 | 48 | 0.6316 | | 1.0996 | 49.0 | 49 | 0.6212 | | 0.548 | 50.0 | 50 | 0.5764 | | 0.548 | 51.0 | 51 | 0.5113 | | 0.548 | 52.0 | 52 | 0.4868 | | 0.548 | 53.0 | 53 | 0.4585 | | 0.548 | 54.0 | 54 | 0.4334 | | 0.548 | 55.0 | 55 | 0.4208 | | 0.548 | 56.0 | 56 | 0.4087 | | 0.548 | 57.0 | 57 | 0.3945 | | 0.548 | 58.0 | 58 | 0.3722 | | 0.548 | 59.0 | 59 | 0.3588 | | 0.548 | 60.0 | 60 | 0.3414 | | 0.548 | 61.0 | 61 | 0.3235 | | 0.548 | 62.0 | 62 | 0.3157 | | 0.548 | 63.0 | 63 | 0.3050 | | 0.548 | 64.0 | 64 | 0.2969 | | 0.548 | 65.0 | 65 | 0.2893 | | 0.548 | 66.0 | 66 | 0.2802 | | 0.548 | 67.0 | 67 | 0.2746 | | 0.548 | 68.0 | 68 | 0.2688 | | 0.548 | 69.0 | 69 | 0.2643 | | 0.548 | 70.0 | 70 | 0.2581 | | 0.548 | 71.0 | 71 | 0.2523 | | 0.548 | 72.0 | 72 | 0.2490 | | 0.548 | 73.0 | 73 | 0.2468 | | 0.548 | 74.0 | 74 | 0.2404 | | 0.1741 | 75.0 | 75 | 0.2394 | | 0.1741 | 76.0 | 76 | 0.2382 | | 0.1741 | 77.0 | 77 | 0.2373 | | 0.1741 | 78.0 | 78 | 0.2366 | | 0.1741 | 79.0 | 79 | 0.2361 | | 0.1741 | 80.0 | 80 | 0.2358 | | 0.1741 | 81.0 | 81 | 0.2355 | | 0.1741 | 82.0 | 82 | 0.2352 | | 0.1741 | 83.0 | 83 | 0.2350 | | 0.1741 | 84.0 | 84 | 0.2348 | | 0.1741 | 85.0 | 85 | 0.2345 | | 0.1741 | 86.0 | 86 | 0.2343 | | 0.1741 | 87.0 | 87 | 0.2342 | | 0.1741 | 88.0 | 88 | 0.2340 | | 0.1741 | 89.0 | 89 | 0.2339 | | 0.1741 | 90.0 | 90 | 0.2337 | | 0.1741 | 91.0 | 91 | 0.2336 | | 0.1741 | 92.0 | 92 | 0.2335 | | 0.1741 | 93.0 | 93 | 0.2334 | | 0.1741 | 94.0 | 94 | 0.2333 | | 0.1741 | 95.0 | 95 | 0.2333 | | 0.1741 | 96.0 | 96 | 0.2332 | | 0.1741 | 97.0 | 97 | 0.2331 | | 0.1741 | 98.0 | 98 | 0.2331 | | 0.1741 | 99.0 | 99 | 0.2331 | | 0.1174 | 100.0 | 100 | 0.2331 | ### Framework versions - PEFT 0.8.1 - Transformers 4.37.2 - Pytorch 2.1.0+cu121 - Datasets 2.16.1 - Tokenizers 0.15.1