---
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-small
tags:
- translation
- generated_from_trainer
metrics:
- bleu
model-index:
- name: t5-small-finetuned-hausa-to-chinese
  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. -->

# t5-small-finetuned-hausa-to-chinese

This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3817
- Bleu: 30.2633
- Gen Len: 3.5559

## 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: 0.0008
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 4000
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.6981        | 1.0   | 846   | 0.2900          | 14.2476 | 3.4917  |
| 0.3149        | 2.0   | 1692  | 0.2639          | 18.6104 | 3.4725  |
| 0.2782        | 3.0   | 2538  | 0.2467          | 9.1092  | 3.2542  |
| 0.2622        | 4.0   | 3384  | 0.2481          | 24.1345 | 3.4047  |
| 0.2428        | 5.0   | 4230  | 0.2529          | 16.9217 | 3.3965  |
| 0.2271        | 6.0   | 5076  | 0.2491          | 27.8491 | 3.5349  |
| 0.2047        | 7.0   | 5922  | 0.2507          | 16.6565 | 3.339   |
| 0.1902        | 8.0   | 6768  | 0.2506          | 25.6462 | 3.5667  |
| 0.1739        | 9.0   | 7614  | 0.2610          | 27.1673 | 3.5916  |
| 0.1587        | 10.0  | 8460  | 0.2438          | 29.306  | 3.5839  |
| 0.1425        | 11.0  | 9306  | 0.2660          | 29.08   | 3.6478  |
| 0.1251        | 12.0  | 10152 | 0.2721          | 29.9148 | 3.4994  |
| 0.1105        | 13.0  | 10998 | 0.2929          | 28.1895 | 3.5526  |
| 0.0956        | 14.0  | 11844 | 0.3010          | 30.552  | 3.5717  |
| 0.083         | 15.0  | 12690 | 0.3307          | 27.9728 | 3.5303  |
| 0.0724        | 16.0  | 13536 | 0.3404          | 27.1874 | 3.5146  |
| 0.0652        | 17.0  | 14382 | 0.3592          | 29.9567 | 3.5529  |
| 0.0568        | 18.0  | 15228 | 0.3774          | 30.5145 | 3.5668  |
| 0.0549        | 19.0  | 16074 | 0.3795          | 30.6604 | 3.5637  |
| 0.0526        | 20.0  | 16920 | 0.3817          | 30.2633 | 3.5559  |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1