---
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_challenge
  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_challenge

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: 1.2142
- Rouge1: 0.2852
- Rouge2: 0.0966
- Rougel: 0.2231
- Rougelsum: 0.2243
- Gen Len: 28.38
- Bleu: 0.0405
- Precisions: 0.0919
- Brevity Penalty: 0.8771
- Length Ratio: 0.8841
- Translation Length: 1068.0
- Reference Length: 1208.0
- Precision: 0.8739
- Recall: 0.8718
- F1: 0.8728
- 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                                                  |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------:|:----------:|:---------------:|:------------:|:------------------:|:----------------:|:---------:|:------:|:------:|:---------------------------------------------------------:|
| 22.2581       | 1.0   | 7    | 6.5353          | 0.084  | 0.0147 | 0.0714 | 0.0714    | 31.0    | 0.0047 | 0.0247     | 0.5558          | 0.63         | 761.0              | 1208.0           | 0.7817    | 0.8234 | 0.8014 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 6.7792        | 2.0   | 14   | 5.1759          | 0.1642 | 0.0129 | 0.13   | 0.1296    | 30.46   | 0.0    | 0.044      | 0.755           | 0.7806       | 943.0              | 1208.0           | 0.8343    | 0.8356 | 0.8349 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 4.5124        | 3.0   | 21   | 3.7445          | 0.2094 | 0.0517 | 0.1669 | 0.1666    | 28.9    | 0.021  | 0.0606     | 0.8336          | 0.846        | 1022.0             | 1208.0           | 0.8516    | 0.8529 | 0.8521 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 3.5042        | 4.0   | 28   | 3.1497          | 0.2314 | 0.0579 | 0.1774 | 0.1772    | 29.1    | 0.0317 | 0.0716     | 0.8537          | 0.8634       | 1043.0             | 1208.0           | 0.855     | 0.8584 | 0.8567 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 2.8574        | 5.0   | 35   | 2.0950          | 0.2342 | 0.0664 | 0.1895 | 0.1897    | 28.34   | 0.0325 | 0.0756     | 0.8584          | 0.8675       | 1048.0             | 1208.0           | 0.8581    | 0.8605 | 0.8593 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 2.0046        | 6.0   | 42   | 1.4599          | 0.2643 | 0.0843 | 0.2074 | 0.2081    | 28.18   | 0.036  | 0.0853     | 0.8678          | 0.8758       | 1058.0             | 1208.0           | 0.8665    | 0.8652 | 0.8658 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 1.4948        | 7.0   | 49   | 1.2786          | 0.2831 | 0.0921 | 0.2203 | 0.2208    | 28.3    | 0.0413 | 0.0893     | 0.8855          | 0.8916       | 1077.0             | 1208.0           | 0.8703    | 0.8681 | 0.8691 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 1.2731        | 8.0   | 56   | 1.2338          | 0.2802 | 0.096  | 0.2204 | 0.2221    | 28.26   | 0.0406 | 0.0893     | 0.8753          | 0.8825       | 1066.0             | 1208.0           | 0.8729    | 0.8705 | 0.8717 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 1.1977        | 9.0   | 63   | 1.2179          | 0.2834 | 0.0991 | 0.2233 | 0.2244    | 28.42   | 0.0409 | 0.0919     | 0.8725          | 0.88         | 1063.0             | 1208.0           | 0.8745    | 0.8722 | 0.8733 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
| 1.1717        | 10.0  | 70   | 1.2142          | 0.2852 | 0.0966 | 0.2231 | 0.2243    | 28.38   | 0.0405 | 0.0919     | 0.8771          | 0.8841       | 1068.0             | 1208.0           | 0.8739    | 0.8718 | 0.8728 | 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