---
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-4_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: 0.5813164556962025
---

<!-- 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-4_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: 2.9420
- Accuracy: 0.5813

## 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: 0.0005
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8732        | 1.0   | 250  | 2.0111          | 0.5939   |
| 1.6142        | 2.0   | 500  | 1.8443          | 0.6051   |
| 1.206         | 3.0   | 750  | 1.9818          | 0.6007   |
| 0.8693        | 4.0   | 1000 | 2.2100          | 0.5941   |
| 0.6023        | 5.0   | 1250 | 2.3756          | 0.5910   |
| 0.4717        | 6.0   | 1500 | 2.5421          | 0.5896   |
| 0.3938        | 7.0   | 1750 | 2.6587          | 0.5891   |
| 0.3697        | 8.0   | 2000 | 2.7532          | 0.5873   |
| 0.3617        | 9.0   | 2250 | 2.7664          | 0.5870   |
| 0.3607        | 10.0  | 2500 | 2.8514          | 0.5867   |
| 0.3414        | 11.0  | 2750 | 2.8932          | 0.5861   |
| 0.3439        | 12.0  | 3000 | 2.9545          | 0.5855   |
| 0.335         | 13.0  | 3250 | 2.8991          | 0.5843   |
| 0.3391        | 14.0  | 3500 | 2.8793          | 0.5840   |
| 0.328         | 15.0  | 3750 | 2.8954          | 0.5851   |
| 0.3351        | 16.0  | 4000 | 2.9140          | 0.5838   |
| 0.3252        | 17.0  | 4250 | 2.9297          | 0.5825   |
| 0.332         | 18.0  | 4500 | 2.9812          | 0.5834   |
| 0.324         | 19.0  | 4750 | 2.9823          | 0.5808   |
| 0.3329        | 20.0  | 5000 | 2.9420          | 0.5813   |


### Framework versions

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