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--- |
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base_model: microsoft/Phi-3.5-mini-instruct |
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library_name: peft |
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license: mit |
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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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model-index: |
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- name: outputs |
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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/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/josh-longenecker1-groundedai/phi3.5-hallucination/runs/re0kg3gs) |
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# outputs |
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This model is a fine-tuned version of [microsoft/Phi-3.5-mini-instruct](https://huggingface.co/microsoft/Phi-3.5-mini-instruct) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3147 |
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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: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_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: 20 |
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- training_steps: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.2594 | 0.5263 | 5 | 2.2572 | |
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| 1.6785 | 1.0526 | 10 | 1.8170 | |
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| 1.6015 | 1.5789 | 15 | 1.4296 | |
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| 1.0556 | 2.1053 | 20 | 1.1199 | |
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| 0.9412 | 2.6316 | 25 | 1.0660 | |
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| 0.8872 | 3.1579 | 30 | 1.0523 | |
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| 0.9157 | 3.6842 | 35 | 1.0713 | |
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| 0.7735 | 4.2105 | 40 | 1.0983 | |
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| 0.6182 | 4.7368 | 45 | 1.0816 | |
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| 0.734 | 5.2632 | 50 | 1.1017 | |
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| 0.4736 | 5.7895 | 55 | 1.2109 | |
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| 0.3138 | 6.3158 | 60 | 1.2195 | |
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| 0.5315 | 6.8421 | 65 | 1.3147 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
