---
base_model: openlm-research/open_llama_3b
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: fine_tuned_model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# fine_tuned_model

This model is a fine-tuned version of [openlm-research/open_llama_3b](https://huggingface.co/openlm-research/open_llama_3b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7834

## 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: 3e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8094        | 0.9615 | 500  | 0.8477          |
| 0.767         | 1.9231 | 1000 | 0.8095          |
| 0.7521        | 2.8846 | 1500 | 0.7917          |
| 0.7529        | 3.8462 | 2000 | 0.7834          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.2
- Pytorch 2.0.1+cu117
- Datasets 3.1.0
- Tokenizers 0.20.3