---
base_model: allenai/PRIMERA
library_name: peft
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: PRIMERA-lora-finetuned
  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. -->

# PRIMERA-lora-finetuned

This model is a fine-tuned version of [allenai/PRIMERA](https://huggingface.co/allenai/PRIMERA) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4326
- Rouge1: 13.8331
- Rouge2: 6.379
- Rougel: 11.3582
- Rougelsum: 13.0901
- Gen Len: 19.0217

## 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: 2e-05
- 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: 16
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 1.9399        | 1.0   | 4725  | 1.6257          | 13.1779 | 5.0715 | 10.6386 | 11.9435   | 19.3478 |
| 1.8124        | 2.0   | 9450  | 1.5723          | 12.8712 | 5.1519 | 10.5072 | 11.9192   | 19.3478 |
| 1.7698        | 3.0   | 14175 | 1.5261          | 13.6339 | 5.5927 | 10.9273 | 12.3707   | 19.3478 |
| 1.7171        | 4.0   | 18900 | 1.4990          | 13.0984 | 6.164  | 10.9698 | 12.1863   | 19.6739 |
| 1.7096        | 5.0   | 23625 | 1.4832          | 12.7164 | 5.4214 | 10.3325 | 11.8134   | 19.3478 |
| 1.6889        | 6.0   | 28350 | 1.4743          | 13.0677 | 4.9162 | 10.3945 | 11.9299   | 19.3478 |
| 1.6667        | 7.0   | 33075 | 1.4652          | 13.8986 | 6.1753 | 10.9896 | 12.8072   | 19.3478 |
| 1.6836        | 8.0   | 37800 | 1.4573          | 13.0179 | 5.5771 | 10.4498 | 12.2198   | 19.0217 |
| 1.6611        | 9.0   | 42525 | 1.4523          | 12.8773 | 5.3502 | 10.294  | 11.9712   | 19.0217 |
| 1.6842        | 10.0  | 47250 | 1.4503          | 13.1982 | 5.0089 | 10.4547 | 12.2554   | 19.0217 |
| 1.6373        | 11.0  | 51975 | 1.4432          | 13.0444 | 5.533  | 10.3895 | 12.3086   | 19.0217 |
| 1.6882        | 12.0  | 56700 | 1.4408          | 13.7092 | 5.9873 | 11.1084 | 12.8159   | 19.3478 |
| 1.6707        | 13.0  | 61425 | 1.4395          | 13.6103 | 6.2231 | 10.7643 | 12.7343   | 19.0217 |
| 1.677         | 14.0  | 66150 | 1.4366          | 13.5232 | 6.3114 | 10.9432 | 12.7234   | 19.0217 |
| 1.6825        | 15.0  | 70875 | 1.4347          | 13.7907 | 6.1456 | 11.0682 | 12.803    | 19.0217 |
| 1.6516        | 16.0  | 75600 | 1.4326          | 13.8331 | 6.379  | 11.3582 | 13.0901   | 19.0217 |


### Framework versions

- PEFT 0.12.0
- Transformers 4.43.3
- Pytorch 2.2.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1