---
library_name: transformers
license: llama2
base_model: meta-llama/Llama-2-7b-chat-hf
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- generator
model-index:
- name: llama_2_o1_10_full
  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_o1_10_full

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 generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6120

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.9433        | 0.0615 | 100  | 0.7648          |
| 0.7768        | 0.1230 | 200  | 0.7311          |
| 0.7448        | 0.1844 | 300  | 0.7125          |
| 0.7336        | 0.2459 | 400  | 0.6952          |
| 0.7224        | 0.3074 | 500  | 0.6859          |
| 0.714         | 0.3689 | 600  | 0.6708          |
| 0.6965        | 0.4304 | 700  | 0.6594          |
| 0.6883        | 0.4919 | 800  | 0.6585          |
| 0.6738        | 0.5533 | 900  | 0.6418          |
| 0.6712        | 0.6148 | 1000 | 0.6328          |
| 0.6633        | 0.6763 | 1100 | 0.6239          |
| 0.6641        | 0.7378 | 1200 | 0.6183          |
| 0.6578        | 0.7993 | 1300 | 0.6167          |
| 0.6519        | 0.8607 | 1400 | 0.6141          |
| 0.652         | 0.9222 | 1500 | 0.6122          |
| 0.655         | 0.9837 | 1600 | 0.6117          |


### Framework versions

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