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-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: 1.6751
- Bleu: 12.5282
- Gen Len: 18.5325

## 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: 0.001
- 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
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 2.6717        | 1.0   | 846   | 1.9694          | 12.1664 | 18.7954 |
| 2.0063        | 2.0   | 1692  | 1.8146          | 10.5635 | 18.8736 |
| 1.8317        | 3.0   | 2538  | 1.7341          | 10.7724 | 18.9023 |
| 1.7706        | 4.0   | 3384  | 1.6942          | 11.676  | 18.0272 |
| 1.6908        | 5.0   | 4230  | 1.6608          | 11.654  | 17.8361 |
| 1.6333        | 6.0   | 5076  | 1.6336          | 11.6008 | 18.0251 |
| 1.5922        | 7.0   | 5922  | 1.6249          | 11.1834 | 18.7068 |
| 1.541         | 8.0   | 6768  | 1.6106          | 12.827  | 18.6533 |
| 1.5121        | 9.0   | 7614  | 1.6082          | 10.873  | 14.6468 |
| 1.4769        | 10.0  | 8460  | 1.5994          | 9.1287  | 15.2999 |
| 1.4358        | 11.0  | 9306  | 1.5943          | 12.1784 | 18.0381 |
| 1.4141        | 12.0  | 10152 | 1.5960          | 12.3004 | 18.6165 |
| 1.3879        | 13.0  | 10998 | 1.6087          | 11.6896 | 18.6615 |
| 1.3526        | 14.0  | 11844 | 1.6015          | 12.2844 | 18.6508 |
| 1.3365        | 15.0  | 12690 | 1.6085          | 11.9235 | 17.9056 |
| 1.3142        | 16.0  | 13536 | 1.6165          | 11.8504 | 17.6737 |
| 1.2846        | 17.0  | 14382 | 1.6198          | 12.4398 | 18.5284 |
| 1.2654        | 18.0  | 15228 | 1.6252          | 12.8486 | 17.7201 |
| 1.2532        | 19.0  | 16074 | 1.6363          | 12.1792 | 17.5936 |
| 1.231         | 20.0  | 16920 | 1.6423          | 12.3326 | 17.7331 |
| 1.2128        | 21.0  | 17766 | 1.6461          | 12.5054 | 18.668  |
| 1.2029        | 22.0  | 18612 | 1.6509          | 12.5588 | 18.5612 |
| 1.1899        | 23.0  | 19458 | 1.6570          | 12.1469 | 17.7074 |
| 1.1804        | 24.0  | 20304 | 1.6620          | 12.4007 | 17.7623 |
| 1.1728        | 25.0  | 21150 | 1.6681          | 12.6017 | 18.5794 |
| 1.1697        | 26.0  | 21996 | 1.6688          | 12.4686 | 18.5296 |
| 1.1661        | 27.0  | 22842 | 1.6720          | 12.5375 | 18.5321 |
| 1.1617        | 28.0  | 23688 | 1.6744          | 12.5354 | 18.5309 |
| 1.1606        | 29.0  | 24534 | 1.6752          | 12.529  | 18.533  |
| 1.1599        | 30.0  | 25380 | 1.6751          | 12.5282 | 18.5325 |


### Framework versions

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