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---
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 |