---
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-chinese-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-chinese-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: 1.6584
- Bleu: 12.1339
- Gen Len: 17.7108

## 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: 5000
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 3.7025        | 1.0   | 846   | 2.6105          | 10.8813 | 18.9939 |
| 2.5979        | 2.0   | 1692  | 2.1871          | 11.8977 | 18.9845 |
| 2.2642        | 3.0   | 2538  | 1.9964          | 10.0898 | 18.9515 |
| 2.0674        | 4.0   | 3384  | 1.8804          | 10.6493 | 17.1889 |
| 1.943         | 5.0   | 4230  | 1.8018          | 10.3424 | 18.9035 |
| 1.8501        | 6.0   | 5076  | 1.7529          | 12.523  | 18.8649 |
| 1.7736        | 7.0   | 5922  | 1.7176          | 11.9247 | 18.8803 |
| 1.711         | 8.0   | 6768  | 1.6823          | 11.623  | 18.3937 |
| 1.6537        | 9.0   | 7614  | 1.6550          | 12.3403 | 18.8995 |
| 1.6083        | 10.0  | 8460  | 1.6398          | 11.774  | 18.6873 |
| 1.5689        | 11.0  | 9306  | 1.6300          | 12.8081 | 18.8652 |
| 1.5314        | 12.0  | 10152 | 1.6279          | 12.2929 | 18.854  |
| 1.4962        | 13.0  | 10998 | 1.6197          | 12.1522 | 17.8497 |
| 1.4655        | 14.0  | 11844 | 1.6050          | 12.0764 | 17.9718 |
| 1.435         | 15.0  | 12690 | 1.6076          | 12.2447 | 17.9524 |
| 1.4047        | 16.0  | 13536 | 1.6048          | 11.4017 | 18.6209 |
| 1.38          | 17.0  | 14382 | 1.6134          | 11.5516 | 18.7405 |
| 1.3513        | 18.0  | 15228 | 1.6105          | 8.6492  | 14.2507 |
| 1.3282        | 19.0  | 16074 | 1.6174          | 12.094  | 17.7717 |
| 1.3052        | 20.0  | 16920 | 1.6239          | 11.5085 | 18.7053 |
| 1.2835        | 21.0  | 17766 | 1.6238          | 12.1588 | 17.7876 |
| 1.2653        | 22.0  | 18612 | 1.6339          | 12.0899 | 17.7112 |
| 1.2503        | 23.0  | 19458 | 1.6399          | 12.1466 | 17.7452 |
| 1.2357        | 24.0  | 20304 | 1.6461          | 9.0097  | 14.3578 |
| 1.2236        | 25.0  | 21150 | 1.6501          | 12.2617 | 17.7143 |
| 1.2139        | 26.0  | 21996 | 1.6528          | 12.1118 | 17.7233 |
| 1.2066        | 27.0  | 22842 | 1.6576          | 12.1435 | 17.7094 |
| 1.2037        | 28.0  | 23688 | 1.6568          | 12.1328 | 17.7133 |
| 1.2           | 29.0  | 24534 | 1.6581          | 12.1289 | 17.7109 |
| 1.1967        | 30.0  | 25380 | 1.6584          | 12.1339 | 17.7108 |


### Framework versions

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