transformers tensorboard safetensors t5 text2text-generation generated_from_trainer base_model:t5-small license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: T5-Small-Sinhala-Sumarization-test3
  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-Sinhala-Sumarization-test3

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: 5.1131
- Rouge1: 0.0507
- Rouge2: 0.0123
- Rougel: 0.0494
- Rougelsum: 0.0492
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 5.9823        | 1.0   | 600  | 5.3762          | 0.0259 | 0.0043 | 0.025  | 0.0248    | 19.0    |
| 5.5041        | 2.0   | 1200 | 5.2242          | 0.0356 | 0.0089 | 0.0352 | 0.0353    | 19.0    |
| 5.4129        | 3.0   | 1800 | 5.1601          | 0.0469 | 0.0104 | 0.0457 | 0.0457    | 19.0    |
| 5.3062        | 4.0   | 2400 | 5.1225          | 0.049  | 0.0119 | 0.0476 | 0.0475    | 19.0    |
| 5.2787        | 5.0   | 3000 | 5.1131          | 0.0507 | 0.0123 | 0.0494 | 0.0492    | 19.0    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
