---
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: AI_Chaperone
  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. -->

# AI_Chaperone

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3785
- Rouge1: 0.1505
- Rouge2: 0.0376
- Rougel: 0.1461
- Rougelsum: 0.1475

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| No log        | 1.0   | 380  | 0.8274          | 0.1131 | 0.0226 | 0.1105 | 0.1109    |
| 1.2345        | 2.0   | 760  | 0.8217          | 0.1146 | 0.0229 | 0.1124 | 0.1133    |
| 0.6137        | 3.0   | 1140 | 0.8487          | 0.1316 | 0.0277 | 0.1260 | 0.1277    |
| 0.4624        | 4.0   | 1520 | 0.9179          | 0.1382 | 0.0286 | 0.1333 | 0.1343    |
| 0.4624        | 5.0   | 1900 | 0.9816          | 0.1430 | 0.0288 | 0.1371 | 0.1391    |
| 0.3444        | 6.0   | 2280 | 1.0601          | 0.1545 | 0.0362 | 0.1510 | 0.1517    |
| 0.2751        | 7.0   | 2660 | 1.1619          | 0.1520 | 0.0335 | 0.1481 | 0.1483    |
| 0.2223        | 8.0   | 3040 | 1.2493          | 0.1515 | 0.0349 | 0.1472 | 0.1475    |
| 0.2223        | 9.0   | 3420 | 1.3379          | 0.1500 | 0.0381 | 0.1451 | 0.1464    |
| 0.1844        | 10.0  | 3800 | 1.3785          | 0.1505 | 0.0376 | 0.1461 | 0.1475    |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3