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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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datasets: |
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- tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3 |
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metrics: |
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- accuracy |
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model-index: |
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- name: lmind_nq_train6000_eval6489_v1_doc_qa_v3_meta-llama_Llama-2-7b-hf_3e-5_lora2 |
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results: |
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- task: |
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name: Causal Language Modeling |
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type: text-generation |
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dataset: |
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name: tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3 |
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type: tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.5965641025641025 |
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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_nq_train6000_eval6489_v1_doc_qa_v3_meta-llama_Llama-2-7b-hf_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 the tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0825 |
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- Accuracy: 0.5966 |
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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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| 1.3948 | 1.0 | 529 | 1.3087 | 0.6132 | |
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| 1.3789 | 2.0 | 1058 | 1.2897 | 0.6146 | |
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| 1.3259 | 3.0 | 1587 | 1.2849 | 0.6179 | |
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| 1.2853 | 4.0 | 2116 | 1.3169 | 0.6159 | |
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| 1.2556 | 5.0 | 2645 | 1.3532 | 0.6132 | |
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| 1.1972 | 6.0 | 3174 | 1.4135 | 0.6126 | |
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| 1.1839 | 7.0 | 3703 | 1.5007 | 0.6081 | |
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| 1.1334 | 8.0 | 4232 | 1.5242 | 0.6074 | |
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| 1.0966 | 9.0 | 4761 | 1.6107 | 0.5803 | |
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| 1.0485 | 10.0 | 5290 | 1.6749 | 0.6049 | |
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| 1.021 | 11.0 | 5819 | 1.7324 | 0.6015 | |
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| 0.9918 | 12.0 | 6348 | 1.7632 | 0.6007 | |
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| 0.947 | 13.0 | 6877 | 1.8303 | 0.6011 | |
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| 0.9376 | 14.0 | 7406 | 1.8873 | 0.5991 | |
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| 0.898 | 15.0 | 7935 | 1.9688 | 0.5976 | |
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| 0.8559 | 16.0 | 8464 | 1.9724 | 0.5988 | |
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| 0.8348 | 17.0 | 8993 | 1.9815 | 0.5714 | |
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| 0.8106 | 18.0 | 9522 | 2.0386 | 0.598 | |
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| 0.7848 | 19.0 | 10051 | 2.0627 | 0.5964 | |
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| 0.745 | 20.0 | 10580 | 2.0825 | 0.5966 | |
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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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