transformers tensorboard safetensors t5 text2text-generation translation generated_from_trainer base_model:google-t5/t5-small base_model:finetune:google-t5/t5-small license:apache-2.0 autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: google-t5/t5-small
library_name: transformers
license: apache-2.0
metrics:
- bleu
tags:
- translation
- generated_from_trainer
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: 0.6851
- Bleu: 71.9442
- Gen Len: 14.3679

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 1.2594        | 1.0   | 1497  | 0.8236          | 59.41   | 14.2172 |
| 0.7848        | 2.0   | 2994  | 0.6581          | 64.4839 | 14.219  |
| 0.6172        | 3.0   | 4491  | 0.5897          | 66.4564 | 14.2357 |
| 0.5151        | 4.0   | 5988  | 0.5619          | 68.0986 | 14.4905 |
| 0.4457        | 5.0   | 7485  | 0.5477          | 69.2175 | 14.4141 |
| 0.3938        | 6.0   | 8982  | 0.5413          | 70.0663 | 14.4059 |
| 0.3555        | 7.0   | 10479 | 0.5338          | 70.1734 | 14.4734 |
| 0.3154        | 8.0   | 11976 | 0.5485          | 70.3692 | 14.3035 |
| 0.2837        | 9.0   | 13473 | 0.5454          | 70.7837 | 14.4556 |
| 0.2507        | 10.0  | 14970 | 0.5616          | 70.976  | 14.3807 |
| 0.2265        | 11.0  | 16467 | 0.5728          | 71.2008 | 14.3692 |
| 0.2041        | 12.0  | 17964 | 0.5808          | 71.4766 | 14.362  |
| 0.1848        | 13.0  | 19461 | 0.5981          | 71.3804 | 14.3114 |
| 0.1715        | 14.0  | 20958 | 0.6122          | 71.43   | 14.4295 |
| 0.1547        | 15.0  | 22455 | 0.6309          | 71.753  | 14.351  |
| 0.1417        | 16.0  | 23952 | 0.6411          | 71.7608 | 14.3513 |
| 0.1267        | 17.0  | 25449 | 0.6612          | 71.93   | 14.4243 |
| 0.1208        | 18.0  | 26946 | 0.6662          | 71.8591 | 14.3486 |
| 0.1076        | 19.0  | 28443 | 0.6799          | 72.0417 | 14.3862 |
| 0.1046        | 20.0  | 29940 | 0.6851          | 71.9442 | 14.3679 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
