---
library_name: transformers
license: apache-2.0
base_model: t5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: samsum_model_t5_small_10_epochs
  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. -->

# samsum_model_t5_small_10_epochs

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: 1.8701
- Rouge1: 0.4055
- Rouge2: 0.1762
- Rougel: 0.3372
- Rougelsum: 0.337
- Gen Len: 16.4738

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 200  | 1.9528          | 0.3844 | 0.1567 | 0.3184 | 0.3182    | 16.1362 |
| No log        | 2.0   | 400  | 1.9221          | 0.3885 | 0.1613 | 0.3212 | 0.321     | 16.3325 |
| 2.0996        | 3.0   | 600  | 1.9072          | 0.3936 | 0.1661 | 0.3264 | 0.3259    | 16.2288 |
| 2.0996        | 4.0   | 800  | 1.8930          | 0.3984 | 0.1678 | 0.3295 | 0.3292    | 16.3375 |
| 2.0297        | 5.0   | 1000 | 1.8860          | 0.4005 | 0.1708 | 0.333  | 0.3329    | 16.355  |
| 2.0297        | 6.0   | 1200 | 1.8780          | 0.4023 | 0.1726 | 0.3341 | 0.3342    | 16.3375 |
| 2.0297        | 7.0   | 1400 | 1.8738          | 0.4025 | 0.1723 | 0.3347 | 0.3346    | 16.4275 |
| 1.9894        | 8.0   | 1600 | 1.8701          | 0.4064 | 0.1757 | 0.3369 | 0.3369    | 16.495  |
| 1.9894        | 9.0   | 1800 | 1.8706          | 0.4061 | 0.1767 | 0.3375 | 0.3375    | 16.4825 |
| 1.9735        | 10.0  | 2000 | 1.8701          | 0.4055 | 0.1762 | 0.3372 | 0.337     | 16.4738 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3