---
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_3e-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: 0.5883291139240506
---

<!-- 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_3e-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: 2.9650
- Accuracy: 0.5883

## 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: 0.0003
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7554        | 1.0   | 250  | 1.7940          | 0.6093   |
| 1.5248        | 2.0   | 500  | 1.8274          | 0.6085   |
| 1.2054        | 3.0   | 750  | 1.9718          | 0.6027   |
| 0.8989        | 4.0   | 1000 | 2.1519          | 0.5987   |
| 0.6306        | 5.0   | 1250 | 2.3293          | 0.5961   |
| 0.4712        | 6.0   | 1500 | 2.5599          | 0.5936   |
| 0.3797        | 7.0   | 1750 | 2.7329          | 0.5936   |
| 0.3527        | 8.0   | 2000 | 2.8185          | 0.5913   |
| 0.3314        | 9.0   | 2250 | 2.8250          | 0.592    |
| 0.3265        | 10.0  | 2500 | 2.9242          | 0.5911   |
| 0.3148        | 11.0  | 2750 | 3.0013          | 0.5912   |
| 0.3184        | 12.0  | 3000 | 2.9315          | 0.5906   |
| 0.3101        | 13.0  | 3250 | 2.9116          | 0.5897   |
| 0.3164        | 14.0  | 3500 | 2.9208          | 0.5902   |
| 0.3074        | 15.0  | 3750 | 2.9385          | 0.5909   |
| 0.3107        | 16.0  | 4000 | 2.9519          | 0.5892   |
| 0.3054        | 17.0  | 4250 | 3.0108          | 0.5898   |
| 0.309         | 18.0  | 4500 | 3.0037          | 0.5904   |
| 0.3005        | 19.0  | 4750 | 3.0279          | 0.5898   |
| 0.3127        | 20.0  | 5000 | 2.9650          | 0.5883   |


### Framework versions

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