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lora/README.md
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---
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license: other
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library_name: peft
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tags:
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- llama-factory
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- lora
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- generated_from_trainer
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base_model: microsoft/Orca-2-7b
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model-index:
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- name: 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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# lora
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This model is a fine-tuned version of [microsoft/Orca-2-7b](https://huggingface.co/microsoft/Orca-2-7b) on the Pretrain_Basic dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4452
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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: 4
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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: 16
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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: 1000
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- num_epochs: 1.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 0.5009 | 0.1586 | 500 | 0.4964 |
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| 0.4641 | 0.3172 | 1000 | 0.4591 |
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| 0.4514 | 0.4758 | 1500 | 0.4516 |
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| 0.4522 | 0.6344 | 2000 | 0.4482 |
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| 0.4436 | 0.7930 | 2500 | 0.4459 |
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| 0.4463 | 0.9516 | 3000 | 0.4452 |
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### Framework versions
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- PEFT 0.10.0
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- Transformers 4.40.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.17.1
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- Tokenizers 0.19.1
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