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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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datasets: |
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- generator |
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base_model: mistralai/Mixtral-8x7B-Instruct-v0.1 |
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model-index: |
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- name: Mixtral-Finetune-Output |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Mixtral-Finetune-Output |
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This model is a fine-tuned version of [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3062 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 1 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 0.03 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.5745 | 0.01 | 10 | 1.4701 | |
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| 1.5372 | 0.02 | 20 | 1.4541 | |
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| 1.4147 | 0.03 | 30 | 1.4433 | |
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| 1.423 | 0.04 | 40 | 1.4366 | |
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| 1.5318 | 0.05 | 50 | 1.4326 | |
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| 1.334 | 0.06 | 60 | 1.4296 | |
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| 1.364 | 0.07 | 70 | 1.4244 | |
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| 1.332 | 0.08 | 80 | 1.4194 | |
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| 1.3742 | 0.09 | 90 | 1.4163 | |
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| 1.4497 | 0.1 | 100 | 1.4124 | |
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| 1.4145 | 0.1 | 110 | 1.4098 | |
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| 1.4224 | 0.11 | 120 | 1.4050 | |
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| 1.4013 | 0.12 | 130 | 1.4017 | |
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| 1.547 | 0.13 | 140 | 1.4020 | |
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| 1.4969 | 0.14 | 150 | 1.3967 | |
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| 1.5716 | 0.15 | 160 | 1.3943 | |
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| 1.3677 | 0.16 | 170 | 1.3915 | |
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| 1.3789 | 0.17 | 180 | 1.3901 | |
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| 1.3188 | 0.18 | 190 | 1.3869 | |
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| 1.3317 | 0.19 | 200 | 1.3846 | |
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| 1.2552 | 0.2 | 210 | 1.3809 | |
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| 1.2584 | 0.21 | 220 | 1.3788 | |
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| 1.3958 | 0.22 | 230 | 1.3776 | |
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| 1.3345 | 0.23 | 240 | 1.3755 | |
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| 1.3562 | 0.24 | 250 | 1.3723 | |
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| 1.343 | 0.25 | 260 | 1.3726 | |
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| 1.3705 | 0.26 | 270 | 1.3695 | |
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| 1.5719 | 0.27 | 280 | 1.3687 | |
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| 1.3634 | 0.28 | 290 | 1.3652 | |
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| 1.4465 | 0.29 | 300 | 1.3668 | |
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| 1.3949 | 0.29 | 310 | 1.3642 | |
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| 1.3147 | 0.3 | 320 | 1.3631 | |
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| 1.368 | 0.31 | 330 | 1.3613 | |
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| 1.3482 | 0.32 | 340 | 1.3603 | |
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| 1.3143 | 0.33 | 350 | 1.3591 | |
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| 1.4717 | 0.34 | 360 | 1.3568 | |
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| 1.2089 | 0.35 | 370 | 1.3555 | |
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| 1.4223 | 0.36 | 380 | 1.3529 | |
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| 1.3895 | 0.37 | 390 | 1.3523 | |
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| 1.309 | 0.38 | 400 | 1.3504 | |
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| 1.3698 | 0.39 | 410 | 1.3487 | |
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| 1.2834 | 0.4 | 420 | 1.3468 | |
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| 1.2747 | 0.41 | 430 | 1.3471 | |
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| 1.3167 | 0.42 | 440 | 1.3460 | |
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| 1.3232 | 0.43 | 450 | 1.3438 | |
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| 1.3628 | 0.44 | 460 | 1.3422 | |
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| 1.3828 | 0.45 | 470 | 1.3417 | |
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| 1.3756 | 0.46 | 480 | 1.3412 | |
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| 1.385 | 0.47 | 490 | 1.3418 | |
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| 1.3622 | 0.48 | 500 | 1.3392 | |
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| 1.3322 | 0.49 | 510 | 1.3381 | |
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| 1.368 | 0.49 | 520 | 1.3365 | |
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| 1.3373 | 0.5 | 530 | 1.3355 | |
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| 1.4931 | 0.51 | 540 | 1.3354 | |
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| 1.3986 | 0.52 | 550 | 1.3333 | |
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| 1.3053 | 0.53 | 560 | 1.3312 | |
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| 1.2736 | 0.54 | 570 | 1.3297 | |
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| 1.2903 | 0.55 | 580 | 1.3298 | |
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| 1.328 | 0.56 | 590 | 1.3290 | |
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| 1.4081 | 0.57 | 600 | 1.3290 | |
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| 1.2852 | 0.58 | 610 | 1.3279 | |
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| 1.3636 | 0.59 | 620 | 1.3268 | |
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| 1.3448 | 0.6 | 630 | 1.3265 | |
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| 1.2061 | 0.61 | 640 | 1.3252 | |
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| 1.3519 | 0.62 | 650 | 1.3244 | |
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| 1.3632 | 0.63 | 660 | 1.3248 | |
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| 1.3784 | 0.64 | 670 | 1.3238 | |
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| 1.3349 | 0.65 | 680 | 1.3216 | |
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| 1.2603 | 0.66 | 690 | 1.3215 | |
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| 1.3566 | 0.67 | 700 | 1.3224 | |
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| 1.316 | 0.68 | 710 | 1.3208 | |
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| 1.1818 | 0.69 | 720 | 1.3203 | |
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| 1.3631 | 0.69 | 730 | 1.3190 | |
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| 1.3234 | 0.7 | 740 | 1.3184 | |
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| 1.2759 | 0.71 | 750 | 1.3177 | |
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| 1.3332 | 0.72 | 760 | 1.3177 | |
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| 1.2764 | 0.73 | 770 | 1.3165 | |
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| 1.2056 | 0.74 | 780 | 1.3155 | |
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| 1.4285 | 0.75 | 790 | 1.3158 | |
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| 1.3733 | 0.76 | 800 | 1.3150 | |
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| 1.2735 | 0.77 | 810 | 1.3143 | |
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| 1.3502 | 0.78 | 820 | 1.3137 | |
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| 1.093 | 0.79 | 830 | 1.3130 | |
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| 1.3451 | 0.8 | 840 | 1.3123 | |
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| 1.2942 | 0.81 | 850 | 1.3119 | |
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| 1.3258 | 0.82 | 860 | 1.3117 | |
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| 1.2139 | 0.83 | 870 | 1.3114 | |
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| 1.2773 | 0.84 | 880 | 1.3109 | |
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| 1.2324 | 0.85 | 890 | 1.3101 | |
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| 1.4134 | 0.86 | 900 | 1.3097 | |
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| 1.3464 | 0.87 | 910 | 1.3095 | |
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| 1.2972 | 0.88 | 920 | 1.3090 | |
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| 1.3305 | 0.88 | 930 | 1.3086 | |
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| 1.3394 | 0.89 | 940 | 1.3082 | |
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| 1.3666 | 0.9 | 950 | 1.3078 | |
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| 1.3703 | 0.91 | 960 | 1.3077 | |
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| 1.3019 | 0.92 | 970 | 1.3077 | |
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| 1.2618 | 0.93 | 980 | 1.3073 | |
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| 1.2808 | 0.94 | 990 | 1.3071 | |
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| 1.2927 | 0.95 | 1000 | 1.3069 | |
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| 1.2688 | 0.96 | 1010 | 1.3067 | |
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| 1.3312 | 0.97 | 1020 | 1.3065 | |
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| 1.2406 | 0.98 | 1030 | 1.3064 | |
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| 1.3341 | 0.99 | 1040 | 1.3062 | |
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| 1.3531 | 1.0 | 1050 | 1.3062 | |
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### Framework versions |
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- PEFT 0.7.1 |
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- Transformers 4.36.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
