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---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: LucaReggiani/t5-small-nlpfinalprojectFinal_2-xsum
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# LucaReggiani/t5-small-nlpfinalprojectFinal_2-xsum
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:
- Train Loss: 3.1437
- Validation Loss: 3.0238
- Train Rouge1: 0.2336
- Train Rouge2: 0.0519
- Train Rougel: 0.1789
- Train Rougelsum: 0.1789
- Train Gen Len: 18.45
- Epoch: 7
## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 3e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.1}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Train Rouge1 | Train Rouge2 | Train Rougel | Train Rougelsum | Train Gen Len | Epoch |
|:----------:|:---------------:|:------------:|:------------:|:------------:|:---------------:|:-------------:|:-----:|
| 3.8777 | 3.3196 | 0.2048 | 0.0442 | 0.1547 | 0.1560 | 18.75 | 0 |
| 3.5167 | 3.1758 | 0.2102 | 0.0457 | 0.1670 | 0.1676 | 18.24 | 1 |
| 3.3968 | 3.1202 | 0.2077 | 0.0439 | 0.1680 | 0.1681 | 18.11 | 2 |
| 3.3297 | 3.0883 | 0.2135 | 0.0444 | 0.1710 | 0.1710 | 18.52 | 3 |
| 3.2789 | 3.0664 | 0.2274 | 0.0500 | 0.1792 | 0.1788 | 18.44 | 4 |
| 3.2279 | 3.0473 | 0.2283 | 0.0510 | 0.1786 | 0.1787 | 18.34 | 5 |
| 3.1857 | 3.0342 | 0.2327 | 0.0534 | 0.1816 | 0.1817 | 18.42 | 6 |
| 3.1437 | 3.0238 | 0.2336 | 0.0519 | 0.1789 | 0.1789 | 18.45 | 7 |
### Framework versions
- Transformers 4.26.1
- TensorFlow 2.11.0
- Datasets 2.10.1
- Tokenizers 0.13.2
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