---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: GreatCaptainNemo/ProLLaMA
metrics:
- precision
- recall
- accuracy
model-index:
- name: prollama-7b-lora-8-remote-homology-filtered
  results: []
---

<!-- 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. -->

# prollama-7b-lora-8-remote-homology-filtered

This model is a fine-tuned version of [GreatCaptainNemo/ProLLaMA](https://huggingface.co/GreatCaptainNemo/ProLLaMA) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4261
- Precision: 0.7980
- Recall: 0.8159
- F1-score: 0.8068
- Accuracy: 0.8042

## 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: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1-score | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:--------:|:--------:|
| 0.4947        | 1.0   | 5313  | 0.4742          | 0.7628    | 0.8081 | 0.7848   | 0.7779   |
| 0.4607        | 2.0   | 10626 | 0.4563          | 0.8163    | 0.7291 | 0.7702   | 0.7820   |
| 0.4377        | 3.0   | 15939 | 0.4466          | 0.8094    | 0.7627 | 0.7854   | 0.7910   |
| 0.4164        | 4.0   | 21252 | 0.4280          | 0.7953    | 0.8151 | 0.8051   | 0.8021   |
| 0.403         | 5.0   | 26565 | 0.4261          | 0.7980    | 0.8159 | 0.8068   | 0.8042   |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1