---
library_name: peft
license: apache-2.0
base_model: allenai/led-base-16384
tags:
- generated_from_trainer
metrics:
- rouge
- bleu
- precision
- recall
- f1
model-index:
- name: Lora_LED_sum_approach
  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. -->

# Lora_LED_sum_approach

This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5646
- Rouge1: 0.4521
- Rouge2: 0.2422
- Rougel: 0.3904
- Rougelsum: 0.3905
- Gen Len: 29.4
- Bleu: 0.1533
- Precisions: 0.2152
- Brevity Penalty: 0.8831
- Length Ratio: 0.8894
- Translation Length: 1086.0
- Reference Length: 1221.0
- Precision: 0.9043
- Recall: 0.9002
- F1: 0.9021
- Hashcode: roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1)

## 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: 0.001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- 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
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Bleu   | Precisions | Brevity Penalty | Length Ratio | Translation Length | Reference Length | Precision | Recall | F1     | Hashcode                                                  |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------:|:----------:|:---------------:|:------------:|:------------------:|:----------------:|:---------:|:------:|:------:|:---------------------------------------------------------:|
| 8.0757        | 1.0   | 7    | 7.6798          | 0.3128 | 0.1085 | 0.253  | 0.2533    | 32.0    | 0.0733 | 0.1062     | 1.0             | 1.0663       | 1302.0             | 1221.0           | 0.8685    | 0.8728 | 0.8706 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 6.5609        | 2.0   | 14   | 5.7642          | 0.4165 | 0.2088 | 0.3627 | 0.3626    | 30.64   | 0.1358 | 0.1742     | 1.0             | 1.036        | 1265.0             | 1221.0           | 0.8922    | 0.8861 | 0.889  | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 4.9145        | 3.0   | 21   | 4.4340          | 0.4234 | 0.2265 | 0.3669 | 0.3685    | 25.84   | 0.1246 | 0.2092     | 0.765           | 0.7887       | 963.0              | 1221.0           | 0.9057    | 0.894  | 0.8996 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 4.0682        | 4.0   | 28   | 3.9241          | 0.4454 | 0.2452 | 0.3952 | 0.3971    | 27.26   | 0.1446 | 0.2209     | 0.8115          | 0.8272       | 1010.0             | 1221.0           | 0.9059    | 0.8983 | 0.9019 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 3.6834        | 5.0   | 35   | 3.7361          | 0.4521 | 0.237  | 0.3828 | 0.3837    | 27.58   | 0.1433 | 0.2137     | 0.8327          | 0.8452       | 1032.0             | 1221.0           | 0.9031    | 0.8973 | 0.9    | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 3.5042        | 6.0   | 42   | 3.6285          | 0.4567 | 0.247  | 0.3901 | 0.3908    | 27.86   | 0.1451 | 0.2184     | 0.8336          | 0.846        | 1033.0             | 1221.0           | 0.9067    | 0.9003 | 0.9033 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 3.4173        | 7.0   | 49   | 3.5881          | 0.4458 | 0.2389 | 0.3839 | 0.3852    | 27.16   | 0.1439 | 0.2226     | 0.7929          | 0.8116       | 991.0              | 1221.0           | 0.9056    | 0.8973 | 0.9013 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 3.3572        | 8.0   | 56   | 3.5698          | 0.4514 | 0.2331 | 0.3836 | 0.3862    | 29.12   | 0.147  | 0.2081     | 0.884           | 0.8903       | 1087.0             | 1221.0           | 0.9026    | 0.8994 | 0.9009 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 3.3165        | 9.0   | 63   | 3.5700          | 0.4592 | 0.2422 | 0.3954 | 0.3957    | 29.28   | 0.1502 | 0.2113     | 0.8922          | 0.8976       | 1096.0             | 1221.0           | 0.9056    | 0.9012 | 0.9033 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 3.3094        | 10.0  | 70   | 3.5646          | 0.4521 | 0.2422 | 0.3904 | 0.3905    | 29.4    | 0.1533 | 0.2152     | 0.8831          | 0.8894       | 1086.0             | 1221.0           | 0.9043    | 0.9002 | 0.9021 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |


### Framework versions

- PEFT 0.15.2
- Transformers 4.53.1
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1