---
library_name: peft
tags:
- generated_from_trainer
datasets:
- scitldr
base_model: meta-llama/Llama-2-7b-hf
model-index:
- name: Llama-Summarization
  results: []
pipeline_tag: summarization
---

<!-- 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 Summarization

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 scitldr dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1108

## 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: 0.0002
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.0965        | 0.25  | 500  | 2.1496          |
| 2.0523        | 0.5   | 1000 | 2.1275          |
| 2.0824        | 0.75  | 1500 | 2.1108          |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2