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--- |
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license: apache-2.0 |
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base_model: teknium/OpenHermes-2.5-Mistral-7B |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: 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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# Enhanced Slither Auditor |
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This model is a fine-tuned version of [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1923 |
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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-06 |
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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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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- total_eval_batch_size: 4 |
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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: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.1498 | 0.0 | 1 | 1.1953 | |
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| 0.321 | 0.1 | 31 | 0.3176 | |
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| 0.2693 | 0.2 | 62 | 0.2712 | |
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| 0.2701 | 0.31 | 93 | 0.2523 | |
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| 0.27 | 0.41 | 124 | 0.2362 | |
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| 0.2244 | 0.51 | 155 | 0.2284 | |
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| 0.2227 | 0.61 | 186 | 0.2260 | |
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| 0.2167 | 0.71 | 217 | 0.2171 | |
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| 0.2098 | 0.81 | 248 | 0.2082 | |
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| 0.1842 | 0.92 | 279 | 0.2047 | |
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| 0.1917 | 1.02 | 310 | 0.2013 | |
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| 0.1639 | 1.12 | 341 | 0.1982 | |
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| 0.1835 | 1.22 | 372 | 0.1968 | |
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| 0.1666 | 1.32 | 403 | 0.1953 | |
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| 0.1694 | 1.43 | 434 | 0.1932 | |
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| 0.1461 | 1.53 | 465 | 0.1929 | |
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| 0.1535 | 1.63 | 496 | 0.1927 | |
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| 0.1419 | 1.73 | 527 | 0.1925 | |
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| 0.1612 | 1.83 | 558 | 0.1923 | |
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| 0.1857 | 1.93 | 589 | 0.1923 | |
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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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