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README.md ADDED
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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: squad_qa_title_v5_full_qaonly_meta-llama_Llama-2-7b-hf_3e-5_lora
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+ results: []
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+ ---
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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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+
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+ # squad_qa_title_v5_full_qaonly_meta-llama_Llama-2-7b-hf_3e-5_lora
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+
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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: 2.7140
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+ - Accuracy: 0.6713
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 32
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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: 50.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 0.99 | 74 | 1.4559 | 0.6859 |
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+ | 1.8449 | 1.99 | 149 | 1.2466 | 0.6966 |
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+ | 1.2465 | 3.0 | 224 | 1.2806 | 0.6943 |
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+ | 1.2465 | 4.0 | 299 | 1.3376 | 0.6928 |
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+ | 1.1239 | 4.99 | 373 | 1.3705 | 0.6927 |
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+ | 1.0214 | 5.99 | 448 | 1.4187 | 0.6898 |
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+ | 0.8757 | 7.0 | 523 | 1.5146 | 0.6850 |
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+ | 0.8757 | 8.0 | 598 | 1.6043 | 0.6820 |
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+ | 0.7243 | 8.99 | 672 | 1.7030 | 0.6797 |
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+ | 0.5566 | 9.99 | 747 | 1.8440 | 0.6742 |
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+ | 0.4482 | 11.0 | 822 | 1.8708 | 0.6738 |
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+ | 0.4482 | 12.0 | 897 | 2.0210 | 0.6723 |
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+ | 0.3721 | 12.99 | 971 | 2.0927 | 0.6706 |
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+ | 0.3134 | 13.99 | 1046 | 2.1836 | 0.6717 |
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+ | 0.2923 | 15.0 | 1121 | 2.2067 | 0.6722 |
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+ | 0.2923 | 16.0 | 1196 | 2.2767 | 0.6720 |
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+ | 0.277 | 16.99 | 1270 | 2.3396 | 0.6715 |
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+ | 0.2604 | 17.99 | 1345 | 2.3341 | 0.6727 |
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+ | 0.2588 | 19.0 | 1420 | 2.2934 | 0.6719 |
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+ | 0.2588 | 20.0 | 1495 | 2.3288 | 0.6720 |
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+ | 0.2545 | 20.99 | 1569 | 2.3674 | 0.6733 |
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+ | 0.246 | 21.99 | 1644 | 2.3575 | 0.6712 |
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+ | 0.2475 | 23.0 | 1719 | 2.4415 | 0.6717 |
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+ | 0.2475 | 24.0 | 1794 | 2.3931 | 0.6724 |
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+ | 0.2441 | 24.99 | 1868 | 2.4622 | 0.6716 |
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+ | 0.2393 | 25.99 | 1943 | 2.4699 | 0.6727 |
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+ | 0.2419 | 27.0 | 2018 | 2.5011 | 0.6721 |
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+ | 0.2419 | 28.0 | 2093 | 2.4473 | 0.6713 |
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+ | 0.2384 | 28.99 | 2167 | 2.5251 | 0.6712 |
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+ | 0.2349 | 29.99 | 2242 | 2.5332 | 0.6706 |
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+ | 0.2362 | 31.0 | 2317 | 2.4678 | 0.6713 |
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+ | 0.2362 | 32.0 | 2392 | 2.4959 | 0.6699 |
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+ | 0.2335 | 32.99 | 2466 | 2.5345 | 0.6692 |
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+ | 0.231 | 33.99 | 2541 | 2.4998 | 0.6716 |
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+ | 0.2323 | 35.0 | 2616 | 2.5296 | 0.6703 |
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+ | 0.2323 | 36.0 | 2691 | 2.6055 | 0.6723 |
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+ | 0.2309 | 36.99 | 2765 | 2.5830 | 0.6727 |
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+ | 0.229 | 37.99 | 2840 | 2.5591 | 0.6710 |
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+ | 0.2293 | 39.0 | 2915 | 2.5690 | 0.6729 |
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+ | 0.2293 | 40.0 | 2990 | 2.5830 | 0.6732 |
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+ | 0.2283 | 40.99 | 3064 | 2.6750 | 0.6712 |
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+ | 0.2248 | 41.99 | 3139 | 2.6572 | 0.6715 |
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+ | 0.2267 | 43.0 | 3214 | 2.6151 | 0.6722 |
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+ | 0.2267 | 44.0 | 3289 | 2.6482 | 0.6722 |
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+ | 0.2252 | 44.99 | 3363 | 2.6898 | 0.6708 |
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+ | 0.224 | 45.99 | 3438 | 2.6339 | 0.6716 |
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+ | 0.2258 | 47.0 | 3513 | 2.6734 | 0.6717 |
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+ | 0.2258 | 48.0 | 3588 | 2.7264 | 0.6713 |
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+ | 0.2249 | 48.99 | 3662 | 2.7045 | 0.6701 |
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+ | 0.2253 | 49.5 | 3700 | 2.7140 | 0.6713 |
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+
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+
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+ ### Framework versions
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+
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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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