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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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# mistral-alpaca-qlora |
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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 mhenrichsen/alpaca_2k_test dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3095 |
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## Model description |
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Standard mistral 7B fine tuned with alpaca format. |
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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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mhenrichsen/alpaca_2k_test |
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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: 0.0002 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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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: 10 |
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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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| 5.5317 | 0.07 | 1 | 5.2182 | |
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| 5.438 | 0.2 | 3 | 4.7897 | |
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| 4.1476 | 0.4 | 6 | 3.4313 | |
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| 3.2037 | 0.6 | 9 | 2.8663 | |
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| 2.7895 | 0.8 | 12 | 2.5112 | |
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| 2.3139 | 1.0 | 15 | 2.1467 | |
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| 2.1672 | 1.2 | 18 | 1.8620 | |
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| 1.9095 | 1.4 | 21 | 1.6519 | |
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| 1.5397 | 1.6 | 24 | 1.5429 | |
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| 1.6327 | 1.8 | 27 | 1.4518 | |
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| 1.3676 | 2.0 | 30 | 1.3892 | |
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| 1.3906 | 2.2 | 33 | 1.3531 | |
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| 1.4096 | 2.4 | 36 | 1.3314 | |
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| 1.3278 | 2.6 | 39 | 1.3165 | |
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| 1.3007 | 2.8 | 42 | 1.3107 | |
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| 1.2848 | 3.0 | 45 | 1.3095 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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