---
license: llama2
base_model: meta-llama/Llama-2-7b-hf
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrachat_200k
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: llama2-7b-sft-full
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# llama2-7b-sft-full

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 HuggingFaceH4/ultrachat_200k and the HuggingFaceH4/ultrafeedback_binarized datasets.
It achieves the following results on the evaluation set:
- Loss: 0.9454

## 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: 8
- total_train_batch_size: 128
- 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: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.9773        | 0.9996 | 1268 | 0.9509          |
| 0.9438        | 2.0    | 2537 | 0.9454          |
| 0.955         | 2.9988 | 3804 | 0.9454          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1