---
base_model: google-t5/t5-base
datasets:
- samsum
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: my-t5-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. -->

# my-t5-summarization-model

This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2478

## 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: 1e-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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 17.2263       | 1.0   | 74   | 20.5598         |
| 10.8174       | 2.0   | 148  | 12.3219         |
| 2.9638        | 3.0   | 222  | 0.6010          |
| 1.4073        | 4.0   | 296  | 0.2598          |
| 1.1503        | 5.0   | 370  | 0.2604          |
| 1.5418        | 6.0   | 444  | 0.2595          |
| 0.6755        | 7.0   | 518  | 0.2574          |
| 0.833         | 8.0   | 592  | 0.2550          |
| 0.5194        | 9.0   | 666  | 0.2549          |
| 0.7579        | 10.0  | 740  | 0.2553          |
| 0.6712        | 11.0  | 814  | 0.2545          |
| 0.6565        | 12.0  | 888  | 0.2540          |
| 0.262         | 13.0  | 962  | 0.2529          |
| 0.3144        | 14.0  | 1036 | 0.2518          |
| 0.6226        | 15.0  | 1110 | 0.2509          |
| 0.5695        | 16.0  | 1184 | 0.2498          |
| 0.2856        | 17.0  | 1258 | 0.2490          |
| 0.2869        | 18.0  | 1332 | 0.2484          |
| 0.6049        | 19.0  | 1406 | 0.2480          |
| 0.6421        | 20.0  | 1480 | 0.2478          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1