---
library_name: transformers
license: other
base_model: meta-llama/Llama-3.1-8B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: llama
  results: []
---

<!-- 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. -->

# llama

This model is a fine-tuned version of [/remote-home1/yli/Model/Generator/Llama3_1_hf/8B/base](https://huggingface.co//remote-home1/yli/Model/Generator/Llama3_1_hf/8B/base) on the 2wikimultihopqa_train, the hotpotqa_train and the musique_train datasets.
It achieves the following results on the evaluation set:
- Loss: 0.1818

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.2053        | 0.1997 | 500  | 0.1904          |
| 0.2035        | 0.3994 | 1000 | 0.1856          |
| 0.1931        | 0.5990 | 1500 | 0.1751          |
| 0.187         | 0.7987 | 2000 | 0.1665          |
| 0.1916        | 0.9984 | 2500 | 0.1609          |
| 0.1085        | 1.1981 | 3000 | 0.1631          |
| 0.1153        | 1.3978 | 3500 | 0.1600          |
| 0.1205        | 1.5974 | 4000 | 0.1545          |
| 0.102         | 1.7971 | 4500 | 0.1496          |
| 0.0737        | 1.9968 | 5000 | 0.1455          |
| 0.0261        | 2.1965 | 5500 | 0.1799          |
| 0.0349        | 2.3962 | 6000 | 0.1782          |
| 0.0269        | 2.5958 | 6500 | 0.1810          |
| 0.0296        | 2.7955 | 7000 | 0.1819          |
| 0.0258        | 2.9952 | 7500 | 0.1818          |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3