---
library_name: transformers
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan-t5-small-compression
  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. -->

# flan-t5-small-compression

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5181
- Rouge1: 0.8820
- Rouge2: 0.7104
- Rougel: 0.8485
- Rougelsum: 0.8488
- Comp Ratio Mean: 0.6611
- Comp Ratio P90: 0.7674
- Pct Violations: 0.0

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adafactor and the args are:
No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Comp Ratio Mean | Comp Ratio P90 | Pct Violations |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:---------------:|:--------------:|:--------------:|
| 1.2576        | 1.0   | 1594  | 0.6457          | 0.8528 | 0.6587 | 0.8197 | 0.8199    | 0.6626          | 0.7736         | 0.0            |
| 0.7688        | 2.0   | 3188  | 0.5727          | 0.8689 | 0.6851 | 0.8345 | 0.8349    | 0.6647          | 0.7694         | 0.0            |
| 0.6591        | 3.0   | 4782  | 0.5405          | 0.8750 | 0.6963 | 0.8413 | 0.8417    | 0.6684          | 0.7692         | 0.0            |
| 0.5957        | 4.0   | 6376  | 0.5333          | 0.8771 | 0.7002 | 0.8438 | 0.8440    | 0.6600          | 0.7660         | 0.0            |
| 0.548         | 5.0   | 7970  | 0.5212          | 0.8792 | 0.7059 | 0.8467 | 0.8470    | 0.6617          | 0.7648         | 0.0004         |
| 0.5139        | 6.0   | 9564  | 0.5196          | 0.8799 | 0.7064 | 0.8472 | 0.8473    | 0.6597          | 0.7636         | 0.0            |
| 0.4862        | 7.0   | 11158 | 0.5144          | 0.8805 | 0.7076 | 0.8473 | 0.8474    | 0.6656          | 0.7705         | 0.0004         |
| 0.466         | 8.0   | 12752 | 0.5157          | 0.8819 | 0.7098 | 0.8489 | 0.8492    | 0.6622          | 0.7674         | 0.0            |
| 0.4499        | 9.0   | 14346 | 0.5156          | 0.8816 | 0.7096 | 0.8486 | 0.8489    | 0.6604          | 0.7660         | 0.0            |
| 0.4393        | 10.0  | 15940 | 0.5181          | 0.8820 | 0.7104 | 0.8485 | 0.8488    | 0.6611          | 0.7674         | 0.0            |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.6.0+cu124
- Datasets 4.4.1
- Tokenizers 0.22.1