---
license: llama2
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_hotpot_train8000_eval7405_v1_qa
metrics:
- accuracy
model-index:
- name: lmind_hotpot_train8000_eval7405_v1_qa_meta-llama_Llama-2-7b-hf_lora2
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: tyzhu/lmind_hotpot_train8000_eval7405_v1_qa
      type: tyzhu/lmind_hotpot_train8000_eval7405_v1_qa
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5903037974683545
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# lmind_hotpot_train8000_eval7405_v1_qa_meta-llama_Llama-2-7b-hf_lora2

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_hotpot_train8000_eval7405_v1_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8216
- Accuracy: 0.5903

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10.0

### Training results

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


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1