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README.md
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---
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license: llama2
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base_model: meta-llama/Llama-2-7b-hf
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: lmind_hotpot_train8000_eval7405_v1_qa_3e-5_lora2
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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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# lmind_hotpot_train8000_eval7405_v1_qa_3e-5_lora2
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This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.9797
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- Accuracy: 0.5824
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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: 3e-05
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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: 4
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 32
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- total_eval_batch_size: 8
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: constant
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- lr_scheduler_warmup_ratio: 0.05
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- num_epochs: 20.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.8255 | 1.0 | 250 | 1.8392 | 0.6054 |
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| 1.7368 | 2.0 | 500 | 1.8111 | 0.6078 |
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| 1.6689 | 3.0 | 750 | 1.8103 | 0.6075 |
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| 1.5555 | 4.0 | 1000 | 1.8414 | 0.6067 |
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| 1.4559 | 5.0 | 1250 | 1.8992 | 0.6038 |
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| 1.3514 | 6.0 | 1500 | 1.9584 | 0.6018 |
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| 1.2491 | 7.0 | 1750 | 2.0300 | 0.6000 |
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| 1.1749 | 8.0 | 2000 | 2.1051 | 0.5982 |
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| 1.0769 | 9.0 | 2250 | 2.1948 | 0.5954 |
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| 1.0134 | 10.0 | 2500 | 2.2515 | 0.5943 |
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| 0.9209 | 11.0 | 2750 | 2.3421 | 0.5921 |
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| 0.8636 | 12.0 | 3000 | 2.4443 | 0.5905 |
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| 0.7866 | 13.0 | 3250 | 2.5574 | 0.588 |
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| 0.7448 | 14.0 | 3500 | 2.5800 | 0.5867 |
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| 0.6709 | 15.0 | 3750 | 2.6912 | 0.5846 |
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| 0.6439 | 16.0 | 4000 | 2.7546 | 0.5853 |
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| 0.5869 | 17.0 | 4250 | 2.7997 | 0.5831 |
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| 0.5596 | 18.0 | 4500 | 2.8435 | 0.5833 |
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| 0.5205 | 19.0 | 4750 | 2.9510 | 0.5833 |
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| 0.5045 | 20.0 | 5000 | 2.9797 | 0.5824 |
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### Framework versions
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- Transformers 4.34.0
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- Pytorch 2.1.0+cu121
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- Datasets 2.18.0
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- Tokenizers 0.14.1
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