---

library_name: transformers
license: other
base_model: meta-llama/Llama-3.1-8B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: SimpleBerry/LLaMA-O1-Base-1127
  results: []

---

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# QuantFactory/LLaMA-O1-Base-1127-GGUF
This is quantized version of [SimpleBerry/LLaMA-O1-Base-1127](https://huggingface.co/SimpleBerry/LLaMA-O1-Base-1127) created using llama.cpp

# Original Model Card


<!-- 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. -->

# SimpleBerry/LLaMA-O1-Base-1127

This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the longcot_pt dataset.

Do not use this model without supervised training, please use [LLaMA-O1-Supervised-1129](https://huggingface.co/SimpleBerry/LLaMA-O1-Supervised-1129) for directly usage.

## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 24
- total_train_batch_size: 24
- total_eval_batch_size: 192
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 4.0

### Training results



### Framework versions

- Transformers 4.46.2
- Pytorch 2.3.1
- Datasets 3.1.0
- Tokenizers 0.20.1