transformers safetensors t5 text2text-generation summarization generated_from_trainer dataset:RMWeerasinghe/BoardPapers-small 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
datasets:
- RMWeerasinghe/BoardPapers-small
license: apache-2.0
metrics:
- rouge
pipeline_tag: summarization
tags:
- summarization
- generated_from_trainer
model-index:
- name: t5-small-finetuned-2048
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# t5-small-finetuned-2048

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: 13.3433
- Rouge1: 0.029
- Rouge2: 0.0023
- Rougel: 0.0267
- Rougelsum: 0.0284

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| No log        | 0.67  | 1    | 25.1883         | 0.0242 | 0.0023 | 0.0218 | 0.0241    |
| No log        | 2.0   | 3    | 23.4392         | 0.0242 | 0.0023 | 0.0218 | 0.0241    |
| No log        | 2.67  | 4    | 22.5166         | 0.0252 | 0.0023 | 0.0229 | 0.0251    |
| No log        | 4.0   | 6    | 20.6643         | 0.0252 | 0.0023 | 0.0229 | 0.0251    |
| No log        | 4.67  | 7    | 19.7334         | 0.0252 | 0.0023 | 0.0229 | 0.0251    |
| No log        | 6.0   | 9    | 17.8137         | 0.0252 | 0.0023 | 0.0229 | 0.0251    |
| No log        | 6.67  | 10   | 17.1117         | 0.0252 | 0.0023 | 0.0229 | 0.0251    |
| No log        | 8.0   | 12   | 16.4384         | 0.0329 | 0.005  | 0.0269 | 0.0324    |
| No log        | 8.67  | 13   | 16.2401         | 0.0329 | 0.005  | 0.0269 | 0.0324    |
| No log        | 10.0  | 15   | 15.9056         | 0.0329 | 0.005  | 0.0269 | 0.0324    |
| No log        | 10.67 | 16   | 15.7547         | 0.0329 | 0.005  | 0.0269 | 0.0324    |
| No log        | 12.0  | 18   | 15.4599         | 0.0329 | 0.005  | 0.0269 | 0.0324    |
| No log        | 12.67 | 19   | 15.3192         | 0.0329 | 0.005  | 0.0269 | 0.0324    |
| 17.3983       | 14.0  | 21   | 15.0513         | 0.0329 | 0.005  | 0.0269 | 0.0324    |
| 17.3983       | 14.67 | 22   | 14.9270         | 0.0367 | 0.005  | 0.0307 | 0.0357    |
| 17.3983       | 16.0  | 24   | 14.7037         | 0.0367 | 0.005  | 0.0307 | 0.0357    |
| 17.3983       | 16.67 | 25   | 14.5987         | 0.0367 | 0.005  | 0.0307 | 0.0357    |
| 17.3983       | 18.0  | 27   | 14.4010         | 0.0367 | 0.005  | 0.0307 | 0.0357    |
| 17.3983       | 18.67 | 28   | 14.3084         | 0.0367 | 0.005  | 0.0307 | 0.0357    |
| 17.3983       | 20.0  | 30   | 14.1348         | 0.0367 | 0.005  | 0.0307 | 0.0357    |
| 17.3983       | 20.67 | 31   | 14.0554         | 0.0367 | 0.005  | 0.0307 | 0.0357    |
| 17.3983       | 22.0  | 33   | 13.9103         | 0.0367 | 0.005  | 0.0307 | 0.0357    |
| 17.3983       | 22.67 | 34   | 13.8446         | 0.029  | 0.0023 | 0.0267 | 0.0284    |
| 17.3983       | 24.0  | 36   | 13.7251         | 0.029  | 0.0023 | 0.0267 | 0.0284    |
| 17.3983       | 24.67 | 37   | 13.6713         | 0.029  | 0.0023 | 0.0267 | 0.0284    |
| 17.3983       | 26.0  | 39   | 13.5781         | 0.029  | 0.0023 | 0.0267 | 0.0284    |
| 13.2153       | 26.67 | 40   | 13.5376         | 0.029  | 0.0023 | 0.0267 | 0.0284    |
| 13.2153       | 28.0  | 42   | 13.4689         | 0.029  | 0.0023 | 0.0267 | 0.0284    |
| 13.2153       | 28.67 | 43   | 13.4408         | 0.029  | 0.0023 | 0.0267 | 0.0284    |
| 13.2153       | 30.0  | 45   | 13.3953         | 0.029  | 0.0023 | 0.0267 | 0.0284    |
| 13.2153       | 30.67 | 46   | 13.3780         | 0.029  | 0.0023 | 0.0267 | 0.0284    |
| 13.2153       | 32.0  | 48   | 13.3538         | 0.029  | 0.0023 | 0.0267 | 0.0284    |
| 13.2153       | 32.67 | 49   | 13.3468         | 0.029  | 0.0023 | 0.0267 | 0.0284    |
| 13.2153       | 33.33 | 50   | 13.3433         | 0.029  | 0.0023 | 0.0267 | 0.0284    |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.1