transformers tensorboard safetensors t5 text2text-generation generated_from_trainer base_model:google-t5/t5-small base_model:finetune:google-t5/t5-small license:apache-2.0 autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: google-t5/t5-small
library_name: transformers
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
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
