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---
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-v2-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-v2-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: 1.1509
- Bleu: 30.0183
- Gen Len: 6.4896

## 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: 0.0006
- 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: 3000
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 1.643         | 1.0   | 1103  | 1.1585          | 24.9091 | 6.7771  |
| 1.1913        | 2.0   | 2206  | 1.0817          | 24.5257 | 6.7541  |
| 1.0945        | 3.0   | 3309  | 1.0737          | 27.3158 | 6.4568  |
| 1.0113        | 4.0   | 4412  | 1.0400          | 27.6138 | 6.6673  |
| 0.9415        | 5.0   | 5515  | 1.0556          | 26.3585 | 6.335   |
| 0.8809        | 6.0   | 6618  | 1.0479          | 25.5111 | 6.4373  |
| 0.8281        | 7.0   | 7721  | 1.0496          | 26.9639 | 6.2402  |
| 0.7805        | 8.0   | 8824  | 1.0687          | 28.3541 | 6.4397  |
| 0.7351        | 9.0   | 9927  | 1.0859          | 28.7719 | 6.4876  |
| 0.6941        | 10.0  | 11030 | 1.1064          | 27.9477 | 6.2022  |
| 0.6621        | 11.0  | 12133 | 1.1114          | 29.7176 | 6.4492  |
| 0.6361        | 12.0  | 13236 | 1.1379          | 29.5086 | 6.4459  |
| 0.6165        | 13.0  | 14339 | 1.1407          | 29.7825 | 6.5262  |
| 0.6039        | 14.0  | 15442 | 1.1498          | 30.0064 | 6.4859  |
| 0.6002        | 15.0  | 16545 | 1.1509          | 30.0183 | 6.4896  |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1