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---
library_name: peft
license: apache-2.0
base_model: google/long-t5-tglobal-base
tags:
- generated_from_trainer
metrics:
- rouge
- bleu
- precision
- recall
- f1
model-index:
- name: Lora_long_T5_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_long_T5_sum_approach
This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8610
- Rouge1: 0.4804
- Rouge2: 0.2605
- Rougel: 0.4126
- Rougelsum: 0.4141
- Gen Len: 28.18
- Bleu: 0.1536
- Precisions: 0.2428
- Brevity Penalty: 0.772
- Length Ratio: 0.7944
- Translation Length: 970.0
- Reference Length: 1221.0
- Precision: 0.914
- Recall: 0.9024
- F1: 0.9081
- 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------:|:----------:|:---------------:|:------------:|:------------------:|:----------------:|:---------:|:------:|:------:|:---------------------------------------------------------:|
| 20.3106 | 1.0 | 7 | 4.7803 | 0.0666 | 0.0125 | 0.0566 | 0.057 | 31.0 | 0.0062 | 0.0248 | 0.5139 | 0.6003 | 733.0 | 1221.0 | 0.7656 | 0.817 | 0.79 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 6.3299 | 2.0 | 14 | 4.0381 | 0.3252 | 0.1232 | 0.2298 | 0.2295 | 30.3 | 0.0656 | 0.1136 | 0.8066 | 0.8231 | 1005.0 | 1221.0 | 0.8607 | 0.8665 | 0.8635 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 3.881 | 3.0 | 21 | 3.2332 | 0.3357 | 0.141 | 0.2638 | 0.2643 | 28.78 | 0.0835 | 0.1391 | 0.8086 | 0.8247 | 1007.0 | 1221.0 | 0.8722 | 0.8719 | 0.872 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 3.138 | 4.0 | 28 | 2.8019 | 0.3883 | 0.1806 | 0.3285 | 0.3283 | 29.14 | 0.0964 | 0.1631 | 0.7978 | 0.8157 | 996.0 | 1221.0 | 0.8856 | 0.8835 | 0.8845 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 2.6873 | 5.0 | 35 | 2.2161 | 0.452 | 0.2271 | 0.3854 | 0.3859 | 27.96 | 0.1276 | 0.2114 | 0.781 | 0.8018 | 979.0 | 1221.0 | 0.9067 | 0.8967 | 0.9016 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 2.0184 | 6.0 | 42 | 1.3080 | 0.463 | 0.2487 | 0.4009 | 0.4028 | 27.62 | 0.1481 | 0.239 | 0.764 | 0.7879 | 962.0 | 1221.0 | 0.9111 | 0.8991 | 0.9049 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 1.3413 | 7.0 | 49 | 0.9692 | 0.4678 | 0.2529 | 0.401 | 0.4025 | 28.06 | 0.1473 | 0.2354 | 0.773 | 0.7952 | 971.0 | 1221.0 | 0.9109 | 0.8996 | 0.9051 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 1.0888 | 8.0 | 56 | 0.8996 | 0.4784 | 0.259 | 0.4102 | 0.4118 | 28.2 | 0.1468 | 0.2363 | 0.775 | 0.7969 | 973.0 | 1221.0 | 0.9126 | 0.9013 | 0.9068 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 0.9722 | 9.0 | 63 | 0.8690 | 0.4824 | 0.262 | 0.4112 | 0.4129 | 28.22 | 0.1523 | 0.2416 | 0.776 | 0.7977 | 974.0 | 1221.0 | 0.9131 | 0.9019 | 0.9074 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 0.948 | 10.0 | 70 | 0.8610 | 0.4804 | 0.2605 | 0.4126 | 0.4141 | 28.18 | 0.1536 | 0.2428 | 0.772 | 0.7944 | 970.0 | 1221.0 | 0.914 | 0.9024 | 0.9081 | 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 |