---
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
metrics:
- bleu
- rouge
model-index:
- name: flanT5_small_EN2AR
  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. -->

[<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/FinalProject_/flanT5/runs/0f48o1me)
[<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/FinalProject_/flanT5/runs/7m7gbfcb)
[<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/FinalProject_/flanT5/runs/7m7gbfcb)
# flanT5_small_EN2AR

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2622
- Bleu: 2.0525
- Rouge: 0.087
- Gen Len: 13.1861

## 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: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 18
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Rouge  | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|
| No log        | 1.0   | 350  | 3.2894          | 2.0707 | 0.0829 | 12.7312 |
| 3.5472        | 2.0   | 700  | 3.2747          | 2.1163 | 0.0825 | 12.7439 |
| 3.4556        | 3.0   | 1050 | 3.2685          | 2.1947 | 0.0869 | 13.6647 |
| 3.4556        | 4.0   | 1400 | 3.2640          | 2.1784 | 0.0857 | 13.9304 |
| 3.3994        | 5.0   | 1750 | 3.2588          | 2.1677 | 0.0877 | 13.19   |
| 3.353         | 6.0   | 2100 | 3.2581          | 2.1906 | 0.0876 | 12.9535 |
| 3.353         | 7.0   | 2450 | 3.2581          | 2.1056 | 0.0873 | 13.232  |
| 3.3052        | 8.0   | 2800 | 3.2579          | 2.0887 | 0.0871 | 13.1443 |
| 3.2749        | 9.0   | 3150 | 3.2561          | 2.0541 | 0.0873 | 12.8396 |
| 3.2725        | 10.0  | 3500 | 3.2567          | 2.1265 | 0.0881 | 12.9237 |
| 3.2725        | 11.0  | 3850 | 3.2592          | 2.103  | 0.0876 | 12.9612 |
| 3.2151        | 12.0  | 4200 | 3.2606          | 2.0482 | 0.087  | 13.1824 |
| 3.2171        | 13.0  | 4550 | 3.2607          | 2.021  | 0.0867 | 13.2216 |
| 3.2171        | 14.0  | 4900 | 3.2609          | 2.0482 | 0.0878 | 13.2296 |
| 3.2013        | 15.0  | 5250 | 3.2614          | 2.0651 | 0.088  | 13.0349 |
| 3.1821        | 16.0  | 5600 | 3.2616          | 2.063  | 0.0879 | 12.9586 |
| 3.1821        | 17.0  | 5950 | 3.2623          | 2.0537 | 0.0869 | 13.1869 |
| 3.1866        | 18.0  | 6300 | 3.2622          | 2.0525 | 0.087  | 13.1861 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1