---
library_name: transformers
license: other
base_model: NousResearch/Meta-Llama-3-8B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: sft
  results: []
datasets:
- clinno/iplaw20240808-json
---

<!-- 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. -->

# sft

This model is a fine-tuned version of [NousResearch/Meta-Llama-3-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Instruct) on the identity and the iplaw20240808 datasets.
It achieves the following results on the evaluation set:
- Loss: 1.0843

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 9.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.3784        | 0.8469 | 500  | 1.4012          |
| 1.1764        | 1.6938 | 1000 | 1.2227          |
| 0.9808        | 2.5408 | 1500 | 1.1500          |
| 0.9778        | 3.3877 | 2000 | 1.1205          |
| 0.8815        | 4.2346 | 2500 | 1.0940          |
| 0.8159        | 5.0815 | 3000 | 1.0748          |
| 0.8317        | 5.9284 | 3500 | 1.0829          |
| 0.7269        | 6.7754 | 4000 | 1.0812          |
| 0.7372        | 7.6223 | 4500 | 1.0817          |
| 0.7366        | 8.4692 | 5000 | 1.0842          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1