---
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-english-to-hausa
  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-english-to-hausa

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: 0.6792
- Bleu: 64.4045
- Gen Len: 14.4721

## 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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 2.5691        | 1.0   | 749  | 1.2064          | 49.1383 | 15.0242 |
| 1.0998        | 2.0   | 1498 | 0.7609          | 61.7452 | 14.4781 |
| 0.7625        | 3.0   | 2247 | 0.6792          | 64.4045 | 14.4721 |


### Framework versions

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