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---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-base-finetuned-scitldr
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. -->
# t5-base-finetuned-scitldr
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1055
- Rouge1: 23.6222
- Rouge2: 10.2432
- Rougel: 19.702
- Rougelsum: 20.9458
- Gen Len: 18.979
## 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: 4e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.4272 | 0.1 | 100 | 3.1951 | 23.0447 | 9.7818 | 19.0676 | 20.1677 | 18.9532 |
| 2.0362 | 0.2 | 200 | 3.1715 | 23.5443 | 10.1156 | 19.5788 | 20.6995 | 18.9483 |
| 2.188 | 0.3 | 300 | 3.1067 | 24.2387 | 10.3059 | 20.0964 | 21.2592 | 18.9338 |
| 2.0312 | 0.4 | 400 | 3.1092 | 23.3168 | 10.1308 | 19.4275 | 20.611 | 18.9742 |
| 2.012 | 0.5 | 500 | 3.1189 | 23.6989 | 10.3005 | 19.7634 | 20.9462 | 18.9758 |
| 2.0581 | 0.6 | 600 | 3.1191 | 23.6818 | 10.2636 | 19.7953 | 20.9935 | 18.9774 |
| 2.0067 | 0.7 | 700 | 3.1297 | 23.8476 | 10.5139 | 19.9696 | 21.1594 | 18.9774 |
| 2.0049 | 0.8 | 800 | 3.1150 | 23.6929 | 10.3243 | 19.7895 | 21.0455 | 18.979 |
| 2.1839 | 0.9 | 900 | 3.1055 | 23.6222 | 10.2432 | 19.702 | 20.9458 | 18.979 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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