README.md

---
library_name: peft
tags:
- generated_from_trainer
datasets:
- patent-classification
metrics:
- accuracy
base_model: NousResearch/Llama-2-7b-hf
model-index:
- name: llama-2-7b-flash-attention2-lora-patent-classification
  results: []
---

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# llama-2-7b-flash-attention2-lora-patent-classification

This model is a fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co./NousResearch/Llama-2-7b-hf) on the patent-classification dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5598
- Accuracy: 0.436
- Precision Macro: 0.4276
- Recall Macro: 0.3658
- F1-score Macro: 0.3707

## 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: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision Macro | Recall Macro | F1-score Macro |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------------:|:------------:|:--------------:|
| 1.4059        | 1.0   | 6250  | 1.9046          | 0.3748   | 0.3815          | 0.3173       | 0.3012         |
| 1.1153        | 2.0   | 12500 | 1.6457          | 0.419    | 0.4162          | 0.3461       | 0.3466         |
| 1.0234        | 3.0   | 18750 | 1.5598          | 0.436    | 0.4276          | 0.3658       | 0.3707         |


### Framework versions

- PEFT 0.7.2.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0