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---
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: Text_Summarization
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. -->
# Text_Summarization
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4199
- Rouge1: 0.2439
- Rouge2: 0.2006
- Rougel: 0.2365
- Rougelsum: 0.2366
- Gen Len: 18.9994
## 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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.9264 | 1.0 | 1580 | 1.6705 | 0.2329 | 0.1842 | 0.223 | 0.223 | 18.9994 |
| 1.8184 | 2.0 | 3160 | 1.5849 | 0.2376 | 0.1894 | 0.2287 | 0.2288 | 18.9988 |
| 1.7427 | 3.0 | 4740 | 1.5382 | 0.2379 | 0.1914 | 0.2296 | 0.2297 | 18.9994 |
| 1.7067 | 4.0 | 6320 | 1.5073 | 0.2397 | 0.1943 | 0.2318 | 0.2318 | 19.0 |
| 1.6783 | 5.0 | 7900 | 1.4873 | 0.2406 | 0.1957 | 0.2329 | 0.2329 | 19.0 |
| 1.6585 | 6.0 | 9480 | 1.4716 | 0.242 | 0.1976 | 0.2343 | 0.2343 | 19.0 |
| 1.6457 | 7.0 | 11060 | 1.4572 | 0.2427 | 0.1988 | 0.2351 | 0.2351 | 19.0 |
| 1.6129 | 8.0 | 12640 | 1.4488 | 0.2433 | 0.1995 | 0.2357 | 0.2358 | 19.0 |
| 1.6014 | 9.0 | 14220 | 1.4405 | 0.2435 | 0.1999 | 0.236 | 0.236 | 19.0 |
| 1.5851 | 10.0 | 15800 | 1.4337 | 0.2439 | 0.2002 | 0.2364 | 0.2365 | 18.9994 |
| 1.5859 | 11.0 | 17380 | 1.4281 | 0.2436 | 0.2 | 0.2362 | 0.2362 | 19.0 |
| 1.573 | 12.0 | 18960 | 1.4247 | 0.244 | 0.2005 | 0.2365 | 0.2366 | 18.9994 |
| 1.5826 | 13.0 | 20540 | 1.4220 | 0.244 | 0.2007 | 0.2365 | 0.2365 | 18.9994 |
| 1.5674 | 14.0 | 22120 | 1.4205 | 0.2439 | 0.2006 | 0.2365 | 0.2365 | 18.9994 |
| 1.572 | 15.0 | 23700 | 1.4199 | 0.2439 | 0.2006 | 0.2365 | 0.2366 | 18.9994 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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