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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_docidx_meta-llama_Llama-2-7b-hf_5e-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_docidx_meta-llama_Llama-2-7b-hf_5e-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: 0.7747
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- Accuracy: 0.7938
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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: 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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| 1.1109 | 1.0 | 839 | 1.3437 | 0.7529 |
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| 1.0723 | 2.0 | 1678 | 1.2988 | 0.7550 |
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| 1.0453 | 3.0 | 2517 | 1.2332 | 0.7577 |
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| 1.0099 | 4.0 | 3357 | 1.2146 | 0.7604 |
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| 0.9553 | 5.0 | 4196 | 1.1671 | 0.7632 |
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| 0.8876 | 6.0 | 5035 | 1.1263 | 0.7655 |
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| 0.8352 | 7.0 | 5874 | 1.0776 | 0.7681 |
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| 0.7872 | 8.0 | 6714 | 1.0745 | 0.7706 |
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| 0.7297 | 9.0 | 7553 | 1.0479 | 0.7730 |
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| 0.6831 | 10.0 | 8392 | 1.0078 | 0.7754 |
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| 0.6397 | 11.0 | 9231 | 0.9763 | 0.7779 |
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| 0.5885 | 12.0 | 10071 | 0.9702 | 0.7803 |
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| 0.5379 | 13.0 | 10910 | 0.9445 | 0.7824 |
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| 0.4996 | 14.0 | 11749 | 0.9087 | 0.7846 |
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| 0.464 | 15.0 | 12588 | 0.8827 | 0.7866 |
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| 0.4225 | 16.0 | 13428 | 0.8886 | 0.7881 |
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| 0.4259 | 17.0 | 14267 | 0.8224 | 0.7898 |
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| 0.361 | 18.0 | 15106 | 0.7985 | 0.7913 |
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| 0.3429 | 19.0 | 15945 | 0.7804 | 0.7930 |
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| 0.305 | 19.99 | 16780 | 0.7747 | 0.7938 |
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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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