---
license: llama2
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_nq_train6000_eval6489_v1_qa
metrics:
- accuracy
model-index:
- name: lmind_nq_train6000_eval6489_v1_qa_5e-4_lora2
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: tyzhu/lmind_nq_train6000_eval6489_v1_qa
      type: tyzhu/lmind_nq_train6000_eval6489_v1_qa
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.3654871794871795
---

<!-- 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_nq_train6000_eval6489_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_nq_train6000_eval6489_v1_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 5.5751
- Accuracy: 0.3655

## 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: 50.0

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 1.43          | 1.0   | 187  | 0.6162   | 1.2683          |
| 1.0285        | 2.0   | 375  | 0.6129   | 1.3220          |
| 0.7318        | 3.0   | 562  | 0.6076   | 1.4645          |
| 0.5898        | 4.0   | 750  | 0.6050   | 1.5454          |
| 0.5309        | 5.0   | 937  | 0.6026   | 1.6439          |
| 0.4985        | 6.0   | 1125 | 0.6034   | 1.7220          |
| 0.5091        | 7.0   | 1312 | 0.6008   | 1.8008          |
| 0.4796        | 8.0   | 1500 | 0.6001   | 1.7782          |
| 0.4453        | 9.0   | 1687 | 0.5985   | 1.8255          |
| 0.448         | 10.0  | 1875 | 0.5931   | 1.7979          |
| 0.4522        | 11.0  | 2062 | 0.5959   | 1.8272          |
| 0.4552        | 12.0  | 2250 | 0.5946   | 1.8670          |
| 0.4551        | 13.0  | 2437 | 0.5950   | 1.8706          |
| 0.4559        | 14.0  | 2625 | 0.5925   | 1.8731          |
| 0.4581        | 15.0  | 2812 | 0.5932   | 1.8531          |
| 0.4535        | 16.0  | 3000 | 0.5923   | 1.9492          |
| 0.4308        | 17.0  | 3187 | 0.5915   | 1.8944          |
| 0.4312        | 18.0  | 3375 | 0.5904   | 1.9315          |
| 0.4372        | 19.0  | 3562 | 0.5899   | 1.9201          |
| 0.4359        | 20.0  | 3750 | 0.5895   | 1.9753          |
| 0.4363        | 21.0  | 3937 | 0.5877   | 1.9932          |
| 0.4404        | 22.0  | 4125 | 0.5866   | 2.0326          |
| 0.4436        | 23.0  | 4312 | 0.5848   | 2.0008          |
| 0.4438        | 24.0  | 4500 | 0.5877   | 2.0186          |
| 0.4233        | 25.0  | 4687 | 0.5863   | 2.0452          |
| 0.4237        | 26.0  | 4875 | 0.5843   | 2.0520          |
| 0.4289        | 27.0  | 5062 | 0.5828   | 2.0817          |
| 0.4325        | 28.0  | 5250 | 0.5833   | 2.0512          |
| 0.4329        | 29.0  | 5437 | 0.5828   | 2.0906          |
| 0.4314        | 30.0  | 5625 | 0.5824   | 2.0403          |
| 0.431         | 31.0  | 5812 | 0.5824   | 2.1194          |
| 0.4318        | 32.0  | 6000 | 0.5829   | 2.0985          |
| 0.414         | 33.0  | 6187 | 0.5805   | 2.1533          |
| 0.4214        | 34.0  | 6375 | 0.5779   | 2.1918          |
| 0.4264        | 35.0  | 6562 | 0.5774   | 2.1835          |
| 0.4361        | 36.0  | 6750 | 0.5771   | 2.1864          |
| 0.4369        | 37.0  | 6937 | 0.5761   | 2.1546          |
| 0.4362        | 38.0  | 7125 | 0.5752   | 2.1423          |
| 0.4322        | 39.0  | 7312 | 0.5778   | 2.1938          |
| 0.4359        | 40.0  | 7500 | 0.5752   | 2.2000          |
| 0.4153        | 41.0  | 7687 | 0.5751   | 2.2344          |
| 0.4195        | 42.0  | 7875 | 0.5747   | 2.2526          |
| 0.9164        | 43.0  | 8062 | 0.5717   | 2.1985          |
| 0.4295        | 44.0  | 8250 | 0.5718   | 2.2145          |
| 0.4298        | 45.0  | 8437 | 0.5714   | 2.2211          |
| 0.4446        | 46.0  | 8625 | 0.5703   | 2.2656          |
| 2.0935        | 47.0  | 8812 | 0.5081   | 2.6962          |
| 3.096         | 48.0  | 9000 | 0.4494   | 3.2961          |
| 2.9615        | 49.0  | 9187 | 0.4241   | 4.3483          |
| 4.5736        | 49.87 | 9350 | 0.3655   | 5.5751          |


### Framework versions

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