---
base_model: minhcrafters/flan-t5-base-minhcrafters
library_name: transformers
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: flan-t5-base-minhcrafters-pychael
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/minhcrafters/flan-t5-base-minhcrafters-pychael/runs/u9lap8kb)
# flan-t5-base-minhcrafters-pychael

This model is a fine-tuned version of [minhcrafters/flan-t5-base-minhcrafters](https://huggingface.co/minhcrafters/flan-t5-base-minhcrafters) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3124
- Rouge1: 34.6663
- Rouge2: 4.3603
- Rougel: 34.6073
- Rougelsum: 34.5948
- Gen Len: 14.1035

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 1.4472        | 1.0   | 1371 | 1.3073          | 32.4779 | 4.0481 | 32.3997 | 32.3826   | 14.6786 |
| 1.2634        | 2.0   | 2742 | 1.2974          | 33.5824 | 4.204  | 33.5354 | 33.5345   | 14.4730 |
| 1.223         | 3.0   | 4113 | 1.2969          | 34.6222 | 3.9502 | 34.6111 | 34.5935   | 14.0926 |
| 1.1697        | 4.0   | 5484 | 1.3094          | 34.1347 | 4.3022 | 34.0956 | 34.0611   | 14.2515 |
| 1.079         | 5.0   | 6855 | 1.3124          | 34.6663 | 4.3603 | 34.6073 | 34.5948   | 14.1035 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1