Model save
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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: squad_qa_no_id_v5_full_meta-llama_Llama-2-7b-hf_1e-4_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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# squad_qa_no_id_v5_full_meta-llama_Llama-2-7b-hf_1e-4_lora
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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: 2.9829
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- Accuracy: 0.6116
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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: 0.0001
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- train_batch_size: 1
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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: 8
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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: 50.0
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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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| 1.6368 | 1.0 | 158 | 1.6276 | 0.624 |
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| 1.0335 | 2.0 | 317 | 1.6646 | 0.6236 |
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| 0.7775 | 3.0 | 475 | 1.7627 | 0.6207 |
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| 0.49 | 4.0 | 634 | 1.9259 | 0.6165 |
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| 0.3885 | 5.0 | 792 | 2.0775 | 0.6135 |
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| 0.2821 | 6.0 | 951 | 2.2256 | 0.6115 |
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| 0.2484 | 7.0 | 1109 | 2.3241 | 0.6106 |
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| 0.2254 | 8.0 | 1268 | 2.3944 | 0.6104 |
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| 0.217 | 9.0 | 1426 | 2.5084 | 0.6102 |
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| 0.2063 | 10.0 | 1585 | 2.5607 | 0.6095 |
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| 0.2004 | 11.0 | 1743 | 2.6099 | 0.6084 |
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| 0.2001 | 12.0 | 1902 | 2.6986 | 0.6072 |
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| 0.1887 | 13.0 | 2060 | 2.7109 | 0.6086 |
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| 0.198 | 14.0 | 2219 | 2.6802 | 0.6098 |
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| 0.1898 | 15.0 | 2377 | 2.6273 | 0.6088 |
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| 0.1956 | 16.0 | 2536 | 2.7269 | 0.6092 |
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| 0.1857 | 17.0 | 2694 | 2.6266 | 0.6112 |
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| 0.1879 | 18.0 | 2853 | 2.6884 | 0.6095 |
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| 0.1927 | 19.0 | 3011 | 2.6882 | 0.6104 |
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| 0.1829 | 20.0 | 3170 | 2.6503 | 0.6105 |
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| 0.1902 | 21.0 | 3328 | 2.7196 | 0.6096 |
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| 0.187 | 22.0 | 3487 | 2.5676 | 0.6096 |
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| 0.1832 | 23.0 | 3645 | 2.7033 | 0.6087 |
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| 0.1925 | 24.0 | 3804 | 2.7632 | 0.6076 |
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| 0.1812 | 25.0 | 3962 | 2.8529 | 0.6066 |
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| 0.1862 | 26.0 | 4121 | 2.7649 | 0.6078 |
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| 0.1841 | 27.0 | 4279 | 2.7719 | 0.6101 |
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| 0.1835 | 28.0 | 4438 | 2.8693 | 0.6087 |
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| 0.1807 | 29.0 | 4596 | 2.9207 | 0.6081 |
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| 0.1773 | 30.0 | 4755 | 2.9250 | 0.6078 |
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| 0.1808 | 31.0 | 4913 | 3.0189 | 0.6090 |
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| 0.1775 | 32.0 | 5072 | 3.0751 | 0.6085 |
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| 0.1775 | 33.0 | 5230 | 3.0890 | 0.6076 |
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| 0.1802 | 34.0 | 5389 | 3.1098 | 0.608 |
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| 0.1794 | 35.0 | 5547 | 3.0633 | 0.6092 |
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| 0.1798 | 36.0 | 5706 | 3.2008 | 0.6068 |
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| 0.1764 | 37.0 | 5864 | 3.1595 | 0.6084 |
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| 0.1794 | 38.0 | 6023 | 2.7637 | 0.6092 |
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| 0.1938 | 39.0 | 6181 | 2.6485 | 0.6093 |
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| 0.1898 | 40.0 | 6340 | 2.7094 | 0.6082 |
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| 0.1912 | 41.0 | 6498 | 2.6494 | 0.6113 |
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| 0.1839 | 42.0 | 6657 | 2.7422 | 0.6103 |
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| 0.1815 | 43.0 | 6815 | 2.7747 | 0.6102 |
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| 0.1725 | 44.0 | 6974 | 2.8100 | 0.6104 |
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| 0.1754 | 45.0 | 7132 | 2.9507 | 0.6105 |
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| 0.1745 | 46.0 | 7291 | 2.9690 | 0.6107 |
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| 0.1758 | 47.0 | 7449 | 2.9188 | 0.6113 |
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| 0.1793 | 48.0 | 7608 | 2.8621 | 0.6125 |
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| 0.1729 | 49.0 | 7766 | 2.9604 | 0.6126 |
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| 0.1793 | 49.84 | 7900 | 2.9829 | 0.6116 |
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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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