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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: pippa-lora |
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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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# pippa-lora |
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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: 1.3494 |
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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: 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: cosine |
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- lr_scheduler_warmup_steps: 40 |
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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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| 1.7313 | 0.05 | 100 | 1.7044 | |
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| 1.68 | 0.11 | 200 | 1.6176 | |
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| 1.5642 | 0.16 | 300 | 1.5538 | |
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| 1.6617 | 0.22 | 400 | 1.4986 | |
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| 1.4733 | 0.27 | 500 | 1.4723 | |
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| 1.4916 | 0.33 | 600 | 1.4427 | |
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| 1.5036 | 0.38 | 700 | 1.4271 | |
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| 1.2385 | 0.44 | 800 | 1.4109 | |
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| 1.4094 | 0.49 | 900 | 1.3968 | |
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| 1.4042 | 0.55 | 1000 | 1.3848 | |
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| 1.3946 | 0.6 | 1100 | 1.3771 | |
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| 1.2523 | 0.66 | 1200 | 1.3692 | |
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| 1.2932 | 0.71 | 1300 | 1.3648 | |
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| 1.346 | 0.77 | 1400 | 1.3609 | |
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| 1.1163 | 0.82 | 1500 | 1.3565 | |
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| 1.4656 | 0.88 | 1600 | 1.3495 | |
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| 1.2698 | 0.93 | 1700 | 1.3484 | |
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| 1.2019 | 0.99 | 1800 | 1.3454 | |
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| 1.3685 | 1.04 | 1900 | 1.3477 | |
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| 1.2248 | 1.1 | 2000 | 1.3488 | |
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| 1.2162 | 1.15 | 2100 | 1.3479 | |
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| 1.0443 | 1.21 | 2200 | 1.3491 | |
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| 1.2445 | 1.26 | 2300 | 1.3460 | |
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| 1.3229 | 1.32 | 2400 | 1.3476 | |
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| 1.3464 | 1.37 | 2500 | 1.3439 | |
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| 1.2651 | 1.43 | 2600 | 1.3439 | |
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| 1.516 | 1.48 | 2700 | 1.3424 | |
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| 1.4323 | 1.54 | 2800 | 1.3413 | |
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| 1.08 | 1.59 | 2900 | 1.3436 | |
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| 1.289 | 1.64 | 3000 | 1.3379 | |
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| 1.1221 | 1.7 | 3100 | 1.3384 | |
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| 1.1895 | 1.75 | 3200 | 1.3376 | |
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| 1.3138 | 1.81 | 3300 | 1.3358 | |
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| 1.3907 | 1.86 | 3400 | 1.3343 | |
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| 1.4544 | 1.92 | 3500 | 1.3351 | |
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| 1.25 | 1.97 | 3600 | 1.3334 | |
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| 1.2682 | 2.03 | 3700 | 1.3452 | |
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| 1.3107 | 2.08 | 3800 | 1.3471 | |
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| 1.2096 | 2.14 | 3900 | 1.3496 | |
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| 1.4503 | 2.19 | 4000 | 1.3503 | |
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| 1.142 | 2.25 | 4100 | 1.3485 | |
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| 0.8439 | 2.3 | 4200 | 1.3490 | |
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| 1.2749 | 2.36 | 4300 | 1.3508 | |
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| 0.9578 | 2.41 | 4400 | 1.3502 | |
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| 1.2203 | 2.47 | 4500 | 1.3496 | |
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| 0.9451 | 2.52 | 4600 | 1.3498 | |
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| 0.9602 | 2.58 | 4700 | 1.3491 | |
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| 0.9501 | 2.63 | 4800 | 1.3491 | |
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| 1.2062 | 2.69 | 4900 | 1.3496 | |
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| 1.1728 | 2.74 | 5000 | 1.3491 | |
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| 1.2506 | 2.8 | 5100 | 1.3494 | |
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| 1.4052 | 2.85 | 5200 | 1.3494 | |
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| 1.2012 | 2.91 | 5300 | 1.3494 | |
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| 1.3141 | 2.96 | 5400 | 1.3494 | |
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### Framework versions |
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- Transformers 4.34.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.0 |
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