---
library_name: transformers
license: other
# base_model: /inspire/hdd/ws-8207e9e2-e733-4eec-a475-cfa1c36480ba/embodied-multimodality/public/yli/workspace/Model/meta-llama/Llama-3.1-8B
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 [/inspire/hdd/ws-8207e9e2-e733-4eec-a475-cfa1c36480ba/embodied-multimodality/public/yli/workspace/Model/meta-llama/Llama-3.1-8B](https://huggingface.co//inspire/hdd/ws-8207e9e2-e733-4eec-a475-cfa1c36480ba/embodied-multimodality/public/yli/workspace/Model/meta-llama/Llama-3.1-8B) on the 2wikimultihopqa_train, the hotpotqa_train and the musique_train datasets.
It achieves the following results on the evaluation set:
- Loss: 0.1784

## 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 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.2074        | 0.1921 | 500  | 0.1999          |
| 0.2202        | 0.3843 | 1000 | 0.1942          |
| 0.1933        | 0.5764 | 1500 | 0.1811          |
| 0.1909        | 0.7686 | 2000 | 0.1720          |
| 0.1637        | 0.9607 | 2500 | 0.1639          |
| 0.0983        | 1.1528 | 3000 | 0.1664          |
| 0.1033        | 1.3450 | 3500 | 0.1602          |
| 0.1145        | 1.5371 | 4000 | 0.1557          |
| 0.105         | 1.7293 | 4500 | 0.1506          |
| 0.1008        | 1.9214 | 5000 | 0.1454          |
| 0.031         | 2.1136 | 5500 | 0.1753          |
| 0.0313        | 2.3057 | 6000 | 0.1777          |
| 0.0323        | 2.4978 | 6500 | 0.1765          |
| 0.0311        | 2.6900 | 7000 | 0.1781          |
| 0.0277        | 2.8821 | 7500 | 0.1787          |


### Framework versions

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