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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
datasets:
- arxiv-summarization
metrics:
- rouge
base_model: google/long-t5-tglobal-base
model-index:
- name: longt5-arvix-finetuned
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. -->
# longt5-arvix-finetuned
This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on the arxiv-summarization dataset.
It achieves the following results on the evaluation set:
- Loss: 30.0035
- Rouge1: 0.0875
- Rouge2: 0.0242
- Rougel: 0.0708
- Rougelsum: 0.0709
- Gen Len: 19.0
## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 29.9697 | 1.0 | 1015 | 31.5396 | 0.089 | 0.0243 | 0.072 | 0.072 | 19.0 |
| 26.9874 | 2.0 | 2031 | 30.1941 | 0.0879 | 0.0242 | 0.0711 | 0.0712 | 19.0 |
| 26.6468 | 3.0 | 3046 | 30.0299 | 0.0877 | 0.0243 | 0.071 | 0.0712 | 19.0 |
| 26.4548 | 4.0 | 4062 | 30.0120 | 0.087 | 0.0239 | 0.0704 | 0.0705 | 19.0 |
| 26.5997 | 5.0 | 5077 | 30.0093 | 0.0875 | 0.0241 | 0.0708 | 0.0709 | 19.0 |
| 26.411 | 6.0 | 6093 | 30.0050 | 0.0875 | 0.024 | 0.0709 | 0.0709 | 19.0 |
| 26.5478 | 7.0 | 7108 | 30.0062 | 0.0876 | 0.0242 | 0.071 | 0.0711 | 19.0 |
| 26.4063 | 8.0 | 8124 | 30.0035 | 0.0876 | 0.0242 | 0.071 | 0.071 | 19.0 |
| 26.4737 | 9.0 | 9139 | 30.0070 | 0.0874 | 0.0241 | 0.0708 | 0.0709 | 19.0 |
| 26.5836 | 10.0 | 10150 | 30.0035 | 0.0875 | 0.0242 | 0.0708 | 0.0709 | 19.0 |
### Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2 |