---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summarizer_samsum_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. -->

# summarizer_samsum_model

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: 0.3992
- Rouge1: 0.4144
- Rouge2: 0.1805
- Rougel: 0.3419
- Rougelsum: 0.3418
- Gen Len: 16.6732

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.4595        | 1.0   | 737  | 0.4170          | 0.3923 | 0.163  | 0.3243 | 0.3242    | 16.1826 |
| 0.4474        | 2.0   | 1474 | 0.4113          | 0.3991 | 0.1685 | 0.3304 | 0.3303    | 16.5925 |
| 0.4416        | 3.0   | 2211 | 0.4092          | 0.4021 | 0.1722 | 0.3337 | 0.3339    | 16.6023 |
| 0.4388        | 4.0   | 2948 | 0.4048          | 0.4062 | 0.1737 | 0.3361 | 0.3361    | 16.5731 |
| 0.4331        | 5.0   | 3685 | 0.4030          | 0.4093 | 0.1758 | 0.3379 | 0.338     | 16.696  |
| 0.4243        | 6.0   | 4422 | 0.4010          | 0.4111 | 0.1778 | 0.3396 | 0.3396    | 16.5728 |
| 0.4234        | 7.0   | 5159 | 0.4000          | 0.4129 | 0.1789 | 0.3406 | 0.3405    | 16.7139 |
| 0.425         | 8.0   | 5896 | 0.3996          | 0.4125 | 0.1797 | 0.3407 | 0.3407    | 16.7089 |
| 0.4247        | 9.0   | 6633 | 0.3993          | 0.4147 | 0.181  | 0.3421 | 0.3422    | 16.6943 |
| 0.4176        | 10.0  | 7370 | 0.3992          | 0.4144 | 0.1805 | 0.3419 | 0.3418    | 16.6732 |


### Framework versions

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