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---
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 |