README.md

---
base_model: meta-llama/Llama-3.2-3B
library_name: peft
license: llama3.2
metrics:
- accuracy
- precision
- recall
- f1
tags:
- generated_from_trainer
model-index:
- name: llama_peft_relation_classification
  results: []
---

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

This model is a fine-tuned version of [meta-llama/Llama-3.2-3B](https://huggingface.co/meta-llama/Llama-3.2-3B) on the I2B2(medical) dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Accuracy: 0.0255
- Precision: 0.0007
- Recall: 0.0255
- F1: 0.0013

## 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: 0.0003
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.0           | 1.0   | 4000  | nan             | 0.0255   | 0.0007    | 0.0255 | 0.0013 |
| 0.0           | 2.0   | 8000  | nan             | 0.0255   | 0.0007    | 0.0255 | 0.0013 |
| 0.0           | 3.0   | 12000 | nan             | 0.0255   | 0.0007    | 0.0255 | 0.0013 |
| 0.0           | 4.0   | 16000 | nan             | 0.0255   | 0.0007    | 0.0255 | 0.0013 |
| 0.0           | 5.0   | 20000 | nan             | 0.0255   | 0.0007    | 0.0255 | 0.0013 |


### Framework versions

- PEFT 0.13.0
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.0
- Tokenizers 0.19.1