---
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
datasets:
- neulab/tldr
metrics:
- rouge
model-index:
- name: BASH-Coder-Flan-T5-base
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: tldr
      type: tldr
      config: data
      split: validation
      args: data
    metrics:
    - name: Rouge1
      type: rouge
      value: 27.0741
---

<!-- 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. -->

# BASH-Coder-Flan-T5-base

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the [neulab/tldr](https://huggingface.co/datasets/neulab/tldr) dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3608
- Rouge1: 27.0741
- Rouge2: 9.3824
- Rougel: 26.133
- Rougelsum: 26.1559
- Gen Len: 15.5767

## 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: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 4.3554        | 1.0   | 802  | 3.5928          | 22.7234 | 6.7951 | 22.0647 | 22.0744   | 15.2363 |
| 3.5335        | 2.0   | 1604 | 3.4654          | 25.7842 | 8.5847 | 24.8207 | 24.8808   | 15.168  |
| 3.3341        | 3.0   | 2406 | 3.4078          | 25.5756 | 8.4456 | 24.706  | 24.7207   | 15.6472 |
| 3.2011        | 4.0   | 3208 | 3.3789          | 26.0638 | 8.6853 | 25.0862 | 25.1223   | 16.2748 |
| 3.1059        | 5.0   | 4010 | 3.3622          | 26.7254 | 9.1138 | 25.7985 | 25.8521   | 15.7366 |
| 3.0336        | 6.0   | 4812 | 3.3662          | 26.4655 | 9.1283 | 25.4587 | 25.5112   | 16.548  |
| 2.9727        | 7.0   | 5614 | 3.3593          | 26.8211 | 9.3045 | 25.8497 | 25.8772   | 15.5431 |
| 2.9298        | 8.0   | 6416 | 3.3643          | 26.8932 | 9.3537 | 25.9444 | 26.0088   | 15.916  |
| 2.9005        | 9.0   | 7218 | 3.3606          | 27.1732 | 9.5661 | 26.1198 | 26.1515   | 15.71   |
| 2.8846        | 10.0  | 8020 | 3.3608          | 27.0741 | 9.3824 | 26.133  | 26.1559   | 15.5767 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0


## Finr-tuning Script

[Google Colaboratory Notebook](https://colab.research.google.com/drive/1VMSVa49xn6O-P6CGNd5AOSoGkPV8D2F_?usp=sharing)