---
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-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: 0.5824050632911393
---

<!-- 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-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: 2.9797
- Accuracy: 0.5824

## 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: 3e-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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8255        | 1.0   | 250  | 1.8392          | 0.6054   |
| 1.7368        | 2.0   | 500  | 1.8111          | 0.6078   |
| 1.6689        | 3.0   | 750  | 1.8103          | 0.6075   |
| 1.5555        | 4.0   | 1000 | 1.8414          | 0.6067   |
| 1.4559        | 5.0   | 1250 | 1.8992          | 0.6038   |
| 1.3514        | 6.0   | 1500 | 1.9584          | 0.6018   |
| 1.2491        | 7.0   | 1750 | 2.0300          | 0.6000   |
| 1.1749        | 8.0   | 2000 | 2.1051          | 0.5982   |
| 1.0769        | 9.0   | 2250 | 2.1948          | 0.5954   |
| 1.0134        | 10.0  | 2500 | 2.2515          | 0.5943   |
| 0.9209        | 11.0  | 2750 | 2.3421          | 0.5921   |
| 0.8636        | 12.0  | 3000 | 2.4443          | 0.5905   |
| 0.7866        | 13.0  | 3250 | 2.5574          | 0.588    |
| 0.7448        | 14.0  | 3500 | 2.5800          | 0.5867   |
| 0.6709        | 15.0  | 3750 | 2.6912          | 0.5846   |
| 0.6439        | 16.0  | 4000 | 2.7546          | 0.5853   |
| 0.5869        | 17.0  | 4250 | 2.7997          | 0.5831   |
| 0.5596        | 18.0  | 4500 | 2.8435          | 0.5833   |
| 0.5205        | 19.0  | 4750 | 2.9510          | 0.5833   |
| 0.5045        | 20.0  | 5000 | 2.9797          | 0.5824   |


### Framework versions

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