---
base_model: meta-llama/Llama-2-7b-chat-hf
library_name: peft
license: llama2
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: llama_2_unsafe_per_class_reflect
  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_2_unsafe_per_class_reflect

This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8179

## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_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
- training_steps: 50

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.3764        | 0.7692 | 5    | 1.8176          |
| 1.6306        | 1.5385 | 10   | 1.2812          |
| 1.2054        | 2.3077 | 15   | 0.9901          |
| 0.9679        | 3.0769 | 20   | 0.8995          |
| 0.8649        | 3.8462 | 25   | 0.8679          |
| 0.8062        | 4.6154 | 30   | 0.8346          |
| 0.8035        | 5.3846 | 35   | 0.8252          |
| 0.7083        | 6.1538 | 40   | 0.8200          |
| 0.703         | 6.9231 | 45   | 0.8188          |
| 0.6968        | 7.6923 | 50   | 0.8179          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1