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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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base_model: mistralai/Mistral-7B-Instruct-v0.3 |
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model-index: |
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- name: finetuned_mistral_on_ads |
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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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# finetuned_mistral_on_ads |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co./mistralai/Mistral-7B-Instruct-v0.3) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5249 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 3.7417 | 0.0444 | 2 | 3.6685 | |
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| 3.6314 | 0.0889 | 4 | 3.2304 | |
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| 3.0686 | 0.1333 | 6 | 2.8771 | |
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| 2.5057 | 0.1778 | 8 | 2.7170 | |
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| 2.5453 | 0.2222 | 10 | 2.5886 | |
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| 2.5759 | 0.2667 | 12 | 2.4625 | |
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| 2.4252 | 0.3111 | 14 | 2.3477 | |
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| 2.4227 | 0.3556 | 16 | 2.2455 | |
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| 1.987 | 0.4 | 18 | 2.1370 | |
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| 2.0229 | 0.4444 | 20 | 2.0484 | |
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| 2.0755 | 0.4889 | 22 | 1.9746 | |
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| 1.9004 | 0.5333 | 24 | 1.9032 | |
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| 1.9381 | 0.5778 | 26 | 1.8405 | |
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| 1.7879 | 0.6222 | 28 | 1.7911 | |
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| 1.7544 | 0.6667 | 30 | 1.7584 | |
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| 1.7485 | 0.7111 | 32 | 1.7290 | |
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| 1.6927 | 0.7556 | 34 | 1.7030 | |
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| 1.8931 | 0.8 | 36 | 1.6825 | |
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| 1.5624 | 0.8444 | 38 | 1.6656 | |
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| 1.7061 | 0.8889 | 40 | 1.6528 | |
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| 1.7288 | 0.9333 | 42 | 1.6426 | |
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| 1.7839 | 0.9778 | 44 | 1.6347 | |
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| 1.5954 | 1.0222 | 46 | 1.6270 | |
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| 1.4288 | 1.0667 | 48 | 1.6177 | |
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| 1.5201 | 1.1111 | 50 | 1.6094 | |
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| 1.5281 | 1.1556 | 52 | 1.6037 | |
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| 1.4132 | 1.2 | 54 | 1.5998 | |
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| 1.4271 | 1.2444 | 56 | 1.5976 | |
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| 1.4778 | 1.2889 | 58 | 1.5952 | |
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| 1.5138 | 1.3333 | 60 | 1.5921 | |
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| 1.4539 | 1.3778 | 62 | 1.5875 | |
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| 1.4293 | 1.4222 | 64 | 1.5823 | |
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| 1.3673 | 1.4667 | 66 | 1.5773 | |
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| 1.5272 | 1.5111 | 68 | 1.5734 | |
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| 1.506 | 1.5556 | 70 | 1.5701 | |
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| 1.2929 | 1.6 | 72 | 1.5669 | |
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| 1.387 | 1.6444 | 74 | 1.5637 | |
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| 1.3375 | 1.6889 | 76 | 1.5609 | |
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| 1.4666 | 1.7333 | 78 | 1.5586 | |
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| 1.2295 | 1.7778 | 80 | 1.5553 | |
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| 1.5195 | 1.8222 | 82 | 1.5521 | |
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| 1.5116 | 1.8667 | 84 | 1.5488 | |
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| 1.2947 | 1.9111 | 86 | 1.5449 | |
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| 1.4651 | 1.9556 | 88 | 1.5399 | |
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| 1.5171 | 2.0 | 90 | 1.5351 | |
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| 1.1823 | 2.0444 | 92 | 1.5312 | |
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| 1.3729 | 2.0889 | 94 | 1.5286 | |
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| 1.2607 | 2.1333 | 96 | 1.5256 | |
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| 1.2048 | 2.1778 | 98 | 1.5237 | |
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| 1.2862 | 2.2222 | 100 | 1.5229 | |
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| 1.2584 | 2.2667 | 102 | 1.5224 | |
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| 1.2285 | 2.3111 | 104 | 1.5223 | |
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| 1.2794 | 2.3556 | 106 | 1.5222 | |
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| 1.2196 | 2.4 | 108 | 1.5227 | |
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| 1.2526 | 2.4444 | 110 | 1.5232 | |
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| 1.2876 | 2.4889 | 112 | 1.5237 | |
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| 1.1812 | 2.5333 | 114 | 1.5247 | |
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| 1.3622 | 2.5778 | 116 | 1.5255 | |
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| 1.229 | 2.6222 | 118 | 1.5261 | |
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| 1.2796 | 2.6667 | 120 | 1.5262 | |
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| 1.2059 | 2.7111 | 122 | 1.5258 | |
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| 1.3327 | 2.7556 | 124 | 1.5257 | |
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| 1.254 | 2.8 | 126 | 1.5257 | |
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| 1.2183 | 2.8444 | 128 | 1.5256 | |
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| 1.1979 | 2.8889 | 130 | 1.5254 | |
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| 1.2558 | 2.9333 | 132 | 1.5251 | |
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| 1.1405 | 2.9778 | 134 | 1.5249 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
