---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: ft-t5-small-on-info-lg-v1
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/asr-africa-research-team/huggingface/runs/ben1m3wk)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/asr-africa-research-team/huggingface/runs/ben1m3wk)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/asr-africa-research-team/huggingface/runs/ben1m3wk)
# ft-t5-small-on-info-lg-v1

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the Luganda Proverbs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5949
- Bleu: 0.2654
- Gen Len: 15.9299

## 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: 0.0001
- 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log        | 1.0   | 177  | 0.5884          | 0.347  | 15.8567 |
| No log        | 2.0   | 354  | 0.5872          | 0.3173 | 16.4809 |
| 0.5373        | 3.0   | 531  | 0.5877          | 0.3232 | 16.2389 |
| 0.5373        | 4.0   | 708  | 0.5878          | 0.3198 | 16.2803 |
| 0.5373        | 5.0   | 885  | 0.5886          | 0.2831 | 14.465  |
| 0.5202        | 6.0   | 1062 | 0.5889          | 0.3702 | 15.4076 |
| 0.5202        | 7.0   | 1239 | 0.5881          | 0.3095 | 16.2325 |
| 0.5202        | 8.0   | 1416 | 0.5880          | 0.2826 | 15.4045 |
| 0.5097        | 9.0   | 1593 | 0.5885          | 0.3264 | 15.9236 |
| 0.5097        | 10.0  | 1770 | 0.5886          | 0.3028 | 14.6592 |
| 0.5097        | 11.0  | 1947 | 0.5872          | 0.2958 | 15.0064 |
| 0.4995        | 12.0  | 2124 | 0.5882          | 0.22   | 14.8631 |
| 0.4995        | 13.0  | 2301 | 0.5876          | 0.2049 | 16.3726 |
| 0.4995        | 14.0  | 2478 | 0.5878          | 0.2635 | 15.8599 |
| 0.4921        | 15.0  | 2655 | 0.5892          | 0.3041 | 15.8248 |
| 0.4921        | 16.0  | 2832 | 0.5881          | 0.2746 | 15.8662 |
| 0.4838        | 17.0  | 3009 | 0.5909          | 0.2713 | 15.8121 |
| 0.4838        | 18.0  | 3186 | 0.5902          | 0.2587 | 15.4076 |
| 0.4838        | 19.0  | 3363 | 0.5917          | 0.3038 | 15.4331 |
| 0.4788        | 20.0  | 3540 | 0.5931          | 0.2837 | 15.3599 |
| 0.4788        | 21.0  | 3717 | 0.5930          | 0.306  | 15.0955 |
| 0.4788        | 22.0  | 3894 | 0.5940          | 0.2973 | 15.7229 |
| 0.4666        | 23.0  | 4071 | 0.5937          | 0.2458 | 16.0096 |
| 0.4666        | 24.0  | 4248 | 0.5936          | 0.2781 | 15.7389 |
| 0.4666        | 25.0  | 4425 | 0.5939          | 0.2998 | 15.5796 |
| 0.4643        | 26.0  | 4602 | 0.5943          | 0.2782 | 15.7293 |
| 0.4643        | 27.0  | 4779 | 0.5942          | 0.2685 | 15.5255 |
| 0.4643        | 28.0  | 4956 | 0.5948          | 0.2687 | 15.6815 |
| 0.4609        | 29.0  | 5133 | 0.5947          | 0.2658 | 15.9363 |
| 0.4609        | 30.0  | 5310 | 0.5949          | 0.2654 | 15.9299 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1