---
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_5e-5_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: 0.5839240506329114
---

<!-- 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_5e-5_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: 3.2298
- Accuracy: 0.5839

## 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: 5e-05
- 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: 20.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.798         | 1.0   | 250  | 1.8213          | 0.6067   |
| 1.7           | 2.0   | 500  | 1.8046          | 0.6077   |
| 1.5869        | 3.0   | 750  | 1.8293          | 0.6071   |
| 1.4349        | 4.0   | 1000 | 1.8974          | 0.6043   |
| 1.3111        | 5.0   | 1250 | 1.9769          | 0.6015   |
| 1.197         | 6.0   | 1500 | 2.0635          | 0.5992   |
| 1.0729        | 7.0   | 1750 | 2.1523          | 0.5975   |
| 0.9833        | 8.0   | 2000 | 2.2640          | 0.5947   |
| 0.8672        | 9.0   | 2250 | 2.3643          | 0.5924   |
| 0.7883        | 10.0  | 2500 | 2.4598          | 0.5908   |
| 0.6879        | 11.0  | 2750 | 2.5669          | 0.5890   |
| 0.6295        | 12.0  | 3000 | 2.7000          | 0.5885   |
| 0.5545        | 13.0  | 3250 | 2.8281          | 0.5851   |
| 0.5208        | 14.0  | 3500 | 2.8794          | 0.5853   |
| 0.4679        | 15.0  | 3750 | 2.9184          | 0.5863   |
| 0.4464        | 16.0  | 4000 | 3.0791          | 0.5852   |
| 0.4136        | 17.0  | 4250 | 3.0832          | 0.5856   |
| 0.4021        | 18.0  | 4500 | 3.0944          | 0.5847   |
| 0.3776        | 19.0  | 4750 | 3.2120          | 0.5828   |
| 0.373         | 20.0  | 5000 | 3.2298          | 0.5839   |


### Framework versions

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