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
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: summarization_model
  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. -->

# summarization_model

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: 2.0680
- Rouge1: 0.1666
- Rouge2: 0.1306
- Rougel: 0.1595
- Rougelsum: 0.1594
- Gen Len: 18.9979

## 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.4854        | 1.0   | 1658 | 2.1906          | 0.1611 | 0.1249 | 0.1533 | 0.1534    | 19.0    |
| 2.3489        | 2.0   | 3316 | 2.1084          | 0.1651 | 0.1288 | 0.1575 | 0.1575    | 18.9988 |
| 2.3034        | 3.0   | 4974 | 2.0739          | 0.1663 | 0.1301 | 0.159  | 0.1589    | 18.9981 |
| 2.2995        | 4.0   | 6632 | 2.0680          | 0.1666 | 0.1306 | 0.1595 | 0.1594    | 18.9979 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
