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license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5_small_SA_SapBERT
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_small_SA_SapBERT
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8542
- Rouge1: 0.1048
- Rouge2: 0.0468
- Rougel: 0.1053
- Rougelsum: 0.1053
- Gen Len: 4.354
## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.9168 | 1.0 | 527 | 1.0769 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.0195 | 2.0 | 1054 | 0.9827 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.9535 | 3.0 | 1581 | 0.9101 | 0.0156 | 0.0053 | 0.0158 | 0.0155 | 3.2389 |
| 0.8636 | 4.0 | 2108 | 0.8914 | 0.0275 | 0.0061 | 0.0272 | 0.0277 | 3.5398 |
| 0.8634 | 5.0 | 2635 | 0.8782 | 0.0508 | 0.0184 | 0.0501 | 0.0511 | 3.885 |
| 0.8494 | 6.0 | 3162 | 0.8714 | 0.0703 | 0.0288 | 0.0695 | 0.0701 | 4.5398 |
| 0.7966 | 7.0 | 3689 | 0.8633 | 0.0715 | 0.0298 | 0.0712 | 0.0714 | 4.3628 |
| 0.8073 | 8.0 | 4216 | 0.8601 | 0.0869 | 0.0398 | 0.0868 | 0.0874 | 4.4336 |
| 0.8308 | 9.0 | 4743 | 0.8578 | 0.0936 | 0.0377 | 0.0933 | 0.0936 | 4.3628 |
| 0.8068 | 10.0 | 5270 | 0.8553 | 0.1014 | 0.0449 | 0.1019 | 0.1014 | 4.2301 |
| 0.8187 | 11.0 | 5797 | 0.8544 | 0.0951 | 0.0381 | 0.0949 | 0.0953 | 4.1681 |
| 0.7627 | 12.0 | 6324 | 0.8542 | 0.1048 | 0.0468 | 0.1053 | 0.1053 | 4.354 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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