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
library_name: transformers
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: my_first_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_first_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: 2.5001
- Rouge1: 0.1369
- Rouge2: 0.0522
- Rougel: 0.1122
- Rougelsum: 0.1123
- Gen Len: 19.0

## 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 62   | 2.7763          | 0.1125 | 0.0313 | 0.0938 | 0.0939    | 19.0    |
| No log        | 2.0   | 124  | 2.5706          | 0.1291 | 0.0444 | 0.1059 | 0.1062    | 19.0    |
| No log        | 3.0   | 186  | 2.5161          | 0.1366 | 0.0516 | 0.1118 | 0.112     | 19.0    |
| No log        | 4.0   | 248  | 2.5001          | 0.1369 | 0.0522 | 0.1122 | 0.1123    | 19.0    |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3
