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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-devices-sum-ver2
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-devices-sum-ver2
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: 0.3679
- Rouge1: 90.6465
- Rouge2: 65.2833
- Rougel: 90.6707
- Rougelsum: 90.7313
- Gen Len: 4.4702
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log | 1.0 | 91 | 1.0957 | 58.9566 | 33.4113 | 58.8004 | 58.8863 | 4.8308 |
| No log | 2.0 | 182 | 0.7017 | 78.9566 | 49.9716 | 78.9338 | 78.9643 | 4.3329 |
| No log | 3.0 | 273 | 0.5386 | 84.8786 | 56.9622 | 84.8204 | 84.9117 | 4.4577 |
| No log | 4.0 | 364 | 0.4693 | 87.9792 | 61.0779 | 87.8795 | 88.0098 | 4.4383 |
| No log | 5.0 | 455 | 0.4273 | 89.4667 | 63.1994 | 89.4169 | 89.5197 | 4.4743 |
| 1.0586 | 6.0 | 546 | 0.4002 | 89.6456 | 63.5041 | 89.6062 | 89.7042 | 4.4452 |
| 1.0586 | 7.0 | 637 | 0.3848 | 89.9993 | 64.2505 | 89.9775 | 90.0651 | 4.423 |
| 1.0586 | 8.0 | 728 | 0.3752 | 90.4249 | 64.819 | 90.4434 | 90.5111 | 4.4799 |
| 1.0586 | 9.0 | 819 | 0.3703 | 90.4689 | 65.0086 | 90.4954 | 90.5632 | 4.4632 |
| 1.0586 | 10.0 | 910 | 0.3679 | 90.6465 | 65.2833 | 90.6707 | 90.7313 | 4.4702 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
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