---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: Text_Summarization_model_15042024
  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_model_15042024

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: 1.5948
- Rouge1: 0.2374
- Rouge2: 0.1905
- Rougel: 0.2302
- Rougelsum: 0.2302
- Gen Len: 19.0

## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.4344        | 0.5   | 500  | 1.9250          | 0.2184 | 0.1678 | 0.2088 | 0.2088    | 18.9925 |
| 2.0598        | 1.0   | 1000 | 1.8118          | 0.2247 | 0.1755 | 0.2155 | 0.2155    | 18.9955 |
| 1.9648        | 1.5   | 1500 | 1.7581          | 0.2303 | 0.1802 | 0.2206 | 0.2206    | 19.0    |
| 1.9119        | 2.0   | 2000 | 1.7214          | 0.2315 | 0.1822 | 0.2221 | 0.2221    | 19.0    |
| 1.8624        | 2.5   | 2500 | 1.6953          | 0.2337 | 0.185  | 0.2253 | 0.2253    | 19.0    |
| 1.8508        | 3.0   | 3000 | 1.6769          | 0.2346 | 0.186  | 0.2266 | 0.2266    | 19.0    |
| 1.8092        | 3.5   | 3500 | 1.6563          | 0.2353 | 0.1871 | 0.2278 | 0.2279    | 19.0    |
| 1.8065        | 4.0   | 4000 | 1.6377          | 0.2359 | 0.188  | 0.2284 | 0.2284    | 19.0    |
| 1.7724        | 4.5   | 4500 | 1.6309          | 0.237  | 0.1895 | 0.2297 | 0.2298    | 19.0    |
| 1.7703        | 5.0   | 5000 | 1.6165          | 0.2376 | 0.1899 | 0.2302 | 0.2303    | 19.0    |
| 1.7468        | 5.5   | 5500 | 1.6082          | 0.2374 | 0.1902 | 0.2303 | 0.2303    | 19.0    |
| 1.7347        | 6.0   | 6000 | 1.5992          | 0.2374 | 0.1906 | 0.2303 | 0.2304    | 19.0    |
| 1.7162        | 6.5   | 6500 | 1.5948          | 0.2374 | 0.1905 | 0.2302 | 0.2302    | 19.0    |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2