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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-devices-sum-ver1
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-ver1
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: 0.2335
- Rouge1: 93.7171
- Rouge2: 73.3058
- Rougel: 93.7211
- Rougelsum: 93.689
- Gen Len: 4.7246
## 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 | 185 | 0.6517 | 83.2503 | 55.7516 | 83.254 | 83.2722 | 4.4729 |
| No log | 2.0 | 370 | 0.4239 | 89.2246 | 65.7477 | 89.2223 | 89.2288 | 4.5575 |
| 1.0224 | 3.0 | 555 | 0.3459 | 91.0524 | 68.4783 | 91.0222 | 91.0312 | 4.6685 |
| 1.0224 | 4.0 | 740 | 0.3023 | 91.9741 | 70.1066 | 91.9886 | 91.9525 | 4.6549 |
| 1.0224 | 5.0 | 925 | 0.2797 | 92.667 | 71.3468 | 92.6706 | 92.6611 | 4.6969 |
| 0.3678 | 6.0 | 1110 | 0.2616 | 93.229 | 72.2805 | 93.222 | 93.1935 | 4.7179 |
| 0.3678 | 7.0 | 1295 | 0.2469 | 93.362 | 72.6985 | 93.3651 | 93.3294 | 4.7111 |
| 0.3678 | 8.0 | 1480 | 0.2401 | 93.5689 | 73.009 | 93.582 | 93.5377 | 4.7192 |
| 0.2902 | 9.0 | 1665 | 0.2350 | 93.7013 | 73.2685 | 93.7256 | 93.684 | 4.724 |
| 0.2902 | 10.0 | 1850 | 0.2335 | 93.7171 | 73.3058 | 93.7211 | 93.689 | 4.7246 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
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