---
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_outcome
  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_outcome

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: 3.7652
- Rouge1: 0.3745
- Rouge2: 0.1523
- Rougel: 0.3056
- Rougelsum: 0.3055
- Gen Len: 25.92
- Bleu: 0.0641
- Precisions: 0.1432
- Brevity Penalty: 0.7677
- Length Ratio: 0.791
- Translation Length: 927.0
- Reference Length: 1172.0
- Precision: 0.8956
- Recall: 0.8832
- F1: 0.8892
- 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                                                  |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------:|:----------:|:---------------:|:------------:|:------------------:|:----------------:|:---------:|:------:|:------:|:---------------------------------------------------------:|
| 8.3925        | 1.0   | 7    | 8.0434          | 0.2138 | 0.043  | 0.174  | 0.1733    | 32.0    | 0.0223 | 0.0541     | 1.0             | 1.1246       | 1318.0             | 1172.0           | 0.8553    | 0.8578 | 0.8564 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 6.8857        | 2.0   | 14   | 6.1890          | 0.3112 | 0.0956 | 0.2638 | 0.2638    | 30.08   | 0.0477 | 0.0915     | 1.0             | 1.0333       | 1211.0             | 1172.0           | 0.8775    | 0.8694 | 0.8733 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 5.1856        | 3.0   | 21   | 4.7196          | 0.3535 | 0.1502 | 0.2855 | 0.2871    | 23.4    | 0.0688 | 0.1552     | 0.7034          | 0.7398       | 867.0              | 1172.0           | 0.9014    | 0.8803 | 0.8906 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 4.2664        | 4.0   | 28   | 4.1945          | 0.354  | 0.1541 | 0.295  | 0.2952    | 23.14   | 0.0781 | 0.1725     | 0.643           | 0.6937       | 813.0              | 1172.0           | 0.904     | 0.8821 | 0.8928 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 3.898         | 5.0   | 35   | 3.9578          | 0.3777 | 0.1653 | 0.3107 | 0.3108    | 25.16   | 0.0912 | 0.1705     | 0.7434          | 0.7713       | 904.0              | 1172.0           | 0.9005    | 0.884  | 0.892  | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 3.6798        | 6.0   | 42   | 3.8411          | 0.368  | 0.1556 | 0.2914 | 0.2907    | 23.92   | 0.0719 | 0.1621     | 0.6836          | 0.7244       | 849.0              | 1172.0           | 0.9039    | 0.8834 | 0.8934 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 3.5743        | 7.0   | 49   | 3.8041          | 0.3678 | 0.1445 | 0.2954 | 0.2956    | 27.28   | 0.0648 | 0.1358     | 0.809           | 0.8251       | 967.0              | 1172.0           | 0.8937    | 0.883  | 0.8883 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 3.5091        | 8.0   | 56   | 3.7772          | 0.371  | 0.1559 | 0.3051 | 0.3061    | 26.3    | 0.0755 | 0.1511     | 0.7709          | 0.7935       | 930.0              | 1172.0           | 0.896     | 0.8833 | 0.8895 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 3.4502        | 9.0   | 63   | 3.7611          | 0.3633 | 0.1495 | 0.3013 | 0.3013    | 25.8    | 0.0653 | 0.1423     | 0.7498          | 0.7765       | 910.0              | 1172.0           | 0.8952    | 0.881  | 0.8879 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 3.4484        | 10.0  | 70   | 3.7652          | 0.3745 | 0.1523 | 0.3056 | 0.3055    | 25.92   | 0.0641 | 0.1432     | 0.7677          | 0.791        | 927.0              | 1172.0           | 0.8956    | 0.8832 | 0.8892 | 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