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---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-MedicoSummarizer
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-MedicoSummarizer
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9737
- Rouge1: 0.3207
- Rouge2: 0.0752
- Rougel: 0.1949
- Rougelsum: 0.1947
- Gen Len: 122.586
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 3.4289 | 1.0 | 625 | 3.0929 | 0.3181 | 0.0722 | 0.1893 | 0.1893 | 122.637 |
| 3.2654 | 2.0 | 1250 | 3.0531 | 0.3199 | 0.0733 | 0.1915 | 0.1916 | 122.072 |
| 3.2288 | 3.0 | 1875 | 3.0245 | 0.317 | 0.0725 | 0.1917 | 0.1917 | 122.153 |
| 3.178 | 4.0 | 2500 | 3.0097 | 0.3161 | 0.0724 | 0.1907 | 0.1907 | 122.398 |
| 3.16 | 5.0 | 3125 | 2.9940 | 0.3162 | 0.0722 | 0.192 | 0.1918 | 122.114 |
| 3.1517 | 6.0 | 3750 | 2.9869 | 0.3165 | 0.0728 | 0.1928 | 0.1926 | 122.652 |
| 3.1429 | 7.0 | 4375 | 2.9815 | 0.3189 | 0.0741 | 0.1935 | 0.1933 | 122.481 |
| 3.1226 | 8.0 | 5000 | 2.9761 | 0.3195 | 0.0755 | 0.194 | 0.1938 | 122.724 |
| 3.1259 | 9.0 | 5625 | 2.9747 | 0.3208 | 0.0755 | 0.1949 | 0.1947 | 122.551 |
| 3.1151 | 10.0 | 6250 | 2.9737 | 0.3207 | 0.0752 | 0.1949 | 0.1947 | 122.586 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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