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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_meta-llama_Llama-2-7b-hf_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_meta-llama_Llama-2-7b-hf_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: 2.8216
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- Accuracy: 0.5903
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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: 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: 10.0
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### Training results
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| Training Loss | Epoch | Step | Accuracy | Validation Loss |
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|:-------------:|:-----:|:----:|:--------:|:---------------:|
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| 1.7795 | 1.0 | 250 | 0.6075 | 1.8062 |
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| 1.6437 | 2.0 | 500 | 1.8114 | 0.6077 |
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| 1.4652 | 3.0 | 750 | 1.8675 | 0.6061 |
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| 1.2631 | 4.0 | 1000 | 1.9843 | 0.6030 |
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| 1.0724 | 5.0 | 1250 | 2.0921 | 0.6001 |
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| 0.8917 | 6.0 | 1500 | 2.2463 | 0.5973 |
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| 0.7235 | 7.0 | 1750 | 2.4073 | 0.5943 |
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| 0.5997 | 8.0 | 2000 | 2.5738 | 0.5931 |
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| 0.4943 | 9.0 | 2250 | 2.6983 | 0.5905 |
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| 0.4381 | 10.0 | 2500 | 2.8216 | 0.5903 |
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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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