---
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_all_aspects
  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_all_aspects

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: 3.2585
- Rouge1: 0.2961
- Rouge2: 0.1042
- Rougel: 0.234
- Rougelsum: 0.2333
- Gen Len: 29.3933
- Bleu: 0.0577
- Precisions: 0.1023
- Brevity Penalty: 0.9031
- Length Ratio: 0.9075
- Translation Length: 3268.0
- Reference Length: 3601.0
- Precision: 0.8752
- Recall: 0.8737
- F1: 0.8744
- 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: 0.002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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: 5
- mixed_precision_training: Native AMP

### 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                                                  |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------:|:----------:|:---------------:|:------------:|:------------------:|:----------------:|:---------:|:------:|:------:|:---------------------------------------------------------:|
| 5.0003        | 1.0   | 38   | 3.3632          | 0.2751 | 0.1031 | 0.2271 | 0.2265    | 26.0267 | 0.0601 | 0.113      | 0.7896          | 0.8089       | 2913.0             | 3601.0           | 0.8795    | 0.8705 | 0.8749 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 3.4616        | 2.0   | 76   | 3.2445          | 0.3023 | 0.104  | 0.237  | 0.2372    | 30.3467 | 0.065  | 0.1086     | 0.9019          | 0.9064       | 3264.0             | 3601.0           | 0.872     | 0.874  | 0.8729 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 3.1933        | 3.0   | 114  | 3.2125          | 0.282  | 0.0998 | 0.2276 | 0.2264    | 29.2733 | 0.0576 | 0.1018     | 0.8859          | 0.892        | 3212.0             | 3601.0           | 0.8732    | 0.8729 | 0.873  | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 3.0156        | 4.0   | 152  | 3.2279          | 0.2848 | 0.1012 | 0.2294 | 0.2287    | 28.92   | 0.0611 | 0.1059     | 0.8862          | 0.8923       | 3213.0             | 3601.0           | 0.8769    | 0.8742 | 0.8755 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 2.874         | 5.0   | 190  | 3.2585          | 0.2961 | 0.1042 | 0.234  | 0.2333    | 29.3933 | 0.0577 | 0.1023     | 0.9031          | 0.9075       | 3268.0             | 3601.0           | 0.8752    | 0.8737 | 0.8744 | 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