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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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- generated_from_trainer |
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base_model: cognitivecomputations/dolphin-2.8-mistral-7b-v02 |
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model-index: |
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- name: fine-tuning-dolphin-mistral-with-webglm-qa-with-lora_1 |
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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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# fine-tuning-dolphin-mistral-with-webglm-qa-with-lora_1 |
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This model is a fine-tuned version of [cognitivecomputations/dolphin-2.8-mistral-7b-v02](https://huggingface.co/cognitivecomputations/dolphin-2.8-mistral-7b-v02) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2999 |
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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: 5e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 5 |
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- total_train_batch_size: 10 |
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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: 60 |
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- training_steps: 700 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.7558 | 0.16 | 10 | 1.4842 | |
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| 1.4966 | 0.32 | 20 | 1.3367 | |
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| 1.2328 | 0.48 | 30 | 1.1282 | |
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| 0.9873 | 0.64 | 40 | 1.0817 | |
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| 0.9661 | 0.8 | 50 | 0.9967 | |
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| 0.8808 | 0.96 | 60 | 0.8844 | |
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| 0.7455 | 1.13 | 70 | 0.7337 | |
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| 0.6018 | 1.29 | 80 | 0.6164 | |
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| 0.4899 | 1.45 | 90 | 0.5440 | |
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| 0.4402 | 1.61 | 100 | 0.4971 | |
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| 0.4154 | 1.77 | 110 | 0.4555 | |
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| 0.4025 | 1.93 | 120 | 0.4238 | |
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| 0.3992 | 2.09 | 130 | 0.4007 | |
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| 0.3585 | 2.25 | 140 | 0.3862 | |
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| 0.3369 | 2.41 | 150 | 0.3666 | |
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| 0.3328 | 2.57 | 160 | 0.3537 | |
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| 0.3216 | 2.73 | 170 | 0.3423 | |
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| 0.2859 | 2.89 | 180 | 0.3303 | |
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| 0.2967 | 3.05 | 190 | 0.3211 | |
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| 0.2933 | 3.22 | 200 | 0.3114 | |
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| 0.2716 | 3.38 | 210 | 0.3097 | |
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| 0.255 | 3.54 | 220 | 0.3053 | |
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| 0.2731 | 3.7 | 230 | 0.2990 | |
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| 0.2729 | 3.86 | 240 | 0.2972 | |
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| 0.2701 | 4.02 | 250 | 0.3030 | |
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| 0.2558 | 4.18 | 260 | 0.3042 | |
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| 0.2612 | 4.34 | 270 | 0.3301 | |
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| 0.3048 | 4.5 | 280 | 0.4564 | |
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| 0.5437 | 4.66 | 290 | 0.7938 | |
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| 1.5888 | 4.82 | 300 | 1.5418 | |
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| 0.6588 | 4.98 | 310 | 0.4630 | |
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| 0.5345 | 5.14 | 320 | 0.9088 | |
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| 1.1475 | 5.31 | 330 | 1.6381 | |
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| 1.6442 | 5.47 | 340 | 2.0495 | |
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| 2.2517 | 5.63 | 350 | 1.7558 | |
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| 0.9492 | 5.79 | 360 | 0.5187 | |
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| 0.3727 | 5.95 | 370 | 0.3763 | |
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| 0.3139 | 6.11 | 380 | 0.3376 | |
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| 0.2896 | 6.27 | 390 | 0.3195 | |
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| 0.283 | 6.43 | 400 | 0.3106 | |
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| 0.2646 | 6.59 | 410 | 0.3105 | |
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| 0.2674 | 6.75 | 420 | 0.3256 | |
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| 0.3482 | 6.91 | 430 | 0.4016 | |
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| 0.4193 | 7.07 | 440 | 0.6300 | |
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| 0.7397 | 7.23 | 450 | 1.0617 | |
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| 1.1954 | 7.4 | 460 | 1.6157 | |
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| 1.6177 | 7.56 | 470 | 1.8019 | |
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| 1.2996 | 7.72 | 480 | 0.9151 | |
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| 0.6605 | 7.88 | 490 | 0.5433 | |
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| 0.416 | 8.04 | 500 | 0.4012 | |
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| 0.3412 | 8.2 | 510 | 0.3685 | |
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| 0.3322 | 8.36 | 520 | 0.3928 | |
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| 0.3516 | 8.52 | 530 | 0.3641 | |
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| 0.3406 | 8.68 | 540 | 0.4061 | |
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| 0.3772 | 8.84 | 550 | 0.4145 | |
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| 0.3695 | 9.0 | 560 | 0.5453 | |
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| 0.5824 | 9.16 | 570 | 0.7332 | |
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| 0.5139 | 9.32 | 580 | 0.4839 | |
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| 0.3798 | 9.49 | 590 | 0.3758 | |
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| 0.319 | 9.65 | 600 | 0.3438 | |
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| 0.3082 | 9.81 | 610 | 0.3301 | |
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| 0.3017 | 9.97 | 620 | 0.3225 | |
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| 0.2862 | 10.13 | 630 | 0.3156 | |
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| 0.2586 | 10.29 | 640 | 0.3109 | |
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| 0.2878 | 10.45 | 650 | 0.3082 | |
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| 0.2766 | 10.61 | 660 | 0.3056 | |
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| 0.2834 | 10.77 | 670 | 0.3042 | |
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| 0.2513 | 10.93 | 680 | 0.3020 | |
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| 0.2762 | 11.09 | 690 | 0.3007 | |
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| 0.28 | 11.25 | 700 | 0.2999 | |
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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 2.0.0 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
