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--- |
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license: apache-2.0 |
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base_model: mistralai/Mistral-7B-v0.1 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: qlora-out |
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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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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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# qlora-out |
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5631 |
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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: 0.0004 |
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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: 4 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 300 |
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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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| 0.8335 | 0.06 | 20 | 0.6429 | |
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| 0.6725 | 0.12 | 40 | 0.5888 | |
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| 0.5927 | 0.18 | 60 | 0.5603 | |
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| 0.5847 | 0.24 | 80 | 0.5362 | |
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| 0.5552 | 0.3 | 100 | 0.5256 | |
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| 0.5511 | 0.36 | 120 | 0.5243 | |
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| 0.5466 | 0.42 | 140 | 0.5102 | |
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| 0.4395 | 0.48 | 160 | 0.5065 | |
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| 0.6854 | 0.54 | 180 | 0.4971 | |
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| 0.7326 | 0.6 | 200 | 0.5150 | |
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| 0.8204 | 0.66 | 220 | 0.5008 | |
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| 0.6009 | 0.72 | 240 | 0.4972 | |
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| 0.4471 | 0.78 | 260 | 0.4944 | |
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| 0.5934 | 0.84 | 280 | 0.5146 | |
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| 0.6574 | 0.9 | 300 | 0.5057 | |
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| 0.4566 | 0.96 | 320 | 0.4880 | |
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| 0.6119 | 1.02 | 340 | 0.5442 | |
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| 0.3779 | 1.08 | 360 | 0.5540 | |
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| 0.4431 | 1.14 | 380 | 0.5375 | |
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| 0.38 | 1.2 | 400 | 0.5541 | |
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| 0.4542 | 1.26 | 420 | 0.5359 | |
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| 0.5392 | 1.32 | 440 | 0.5394 | |
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| 0.2573 | 1.38 | 460 | 0.5318 | |
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| 0.5441 | 1.44 | 480 | 0.5201 | |
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| 0.3758 | 1.5 | 500 | 0.5147 | |
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| 0.4403 | 1.56 | 520 | 0.5134 | |
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| 0.3308 | 1.62 | 540 | 0.5289 | |
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| 0.4604 | 1.68 | 560 | 0.5205 | |
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| 0.4479 | 1.74 | 580 | 0.5340 | |
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| 0.521 | 1.8 | 600 | 0.5094 | |
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| 0.32 | 1.86 | 620 | 0.4995 | |
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| 0.3984 | 1.92 | 640 | 0.4878 | |
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| 0.3799 | 1.98 | 660 | 0.4826 | |
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| 0.1484 | 2.04 | 680 | 0.7261 | |
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| 0.3305 | 2.1 | 700 | 0.6187 | |
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| 0.1477 | 2.16 | 720 | 0.5499 | |
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| 0.176 | 2.22 | 740 | 0.5796 | |
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| 0.1892 | 2.28 | 760 | 0.5717 | |
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| 0.1921 | 2.34 | 780 | 0.5416 | |
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| 0.1366 | 2.4 | 800 | 0.5866 | |
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| 0.1726 | 2.46 | 820 | 0.5562 | |
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| 0.1264 | 2.51 | 840 | 0.5621 | |
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| 0.2054 | 2.57 | 860 | 0.5678 | |
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| 0.1722 | 2.63 | 880 | 0.5573 | |
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| 0.2399 | 2.69 | 900 | 0.5553 | |
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| 0.229 | 2.75 | 920 | 0.5565 | |
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| 0.1876 | 2.81 | 940 | 0.5609 | |
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| 0.2281 | 2.87 | 960 | 0.5633 | |
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| 0.1727 | 2.93 | 980 | 0.5645 | |
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| 0.3536 | 2.99 | 1000 | 0.5631 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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