---
library_name: transformers
base_model: mt5_small/lg_inf_en
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: mt5_small_lg_inf_en
  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. -->

# mt5_small_lg_inf_en

This model is a fine-tuned version of [mt5_small/lg_inf_en](https://huggingface.co/mt5_small/lg_inf_en) on the Luganda Informal Data dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4301
- Bleu: 0.3034
- Gen Len: 8.1551

## 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: 2e-05
- 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   | 138  | 0.4671          | 0.0646 | 9.4449  |
| No log        | 2.0   | 276  | 0.4562          | 0.1318 | 7.8898  |
| No log        | 3.0   | 414  | 0.4511          | 0.2119 | 7.9878  |
| 0.4729        | 4.0   | 552  | 0.4476          | 0.2133 | 8.1184  |
| 0.4729        | 5.0   | 690  | 0.4451          | 0.2128 | 8.0816  |
| 0.4729        | 6.0   | 828  | 0.4433          | 0.3272 | 7.9224  |
| 0.4729        | 7.0   | 966  | 0.4415          | 0.3383 | 7.6571  |
| 0.4479        | 8.0   | 1104 | 0.4401          | 0.3281 | 7.5347  |
| 0.4479        | 9.0   | 1242 | 0.4390          | 0.3296 | 7.4286  |
| 0.4479        | 10.0  | 1380 | 0.4378          | 0.3157 | 7.6     |
| 0.4418        | 11.0  | 1518 | 0.4367          | 0.3288 | 7.4327  |
| 0.4418        | 12.0  | 1656 | 0.4360          | 0.316  | 7.4857  |
| 0.4418        | 13.0  | 1794 | 0.4350          | 0.3167 | 7.4898  |
| 0.4418        | 14.0  | 1932 | 0.4342          | 0.3161 | 7.698   |
| 0.4347        | 15.0  | 2070 | 0.4337          | 0.316  | 7.849   |
| 0.4347        | 16.0  | 2208 | 0.4333          | 0.3177 | 7.6735  |
| 0.4347        | 17.0  | 2346 | 0.4326          | 0.3174 | 7.8082  |
| 0.4347        | 18.0  | 2484 | 0.4324          | 0.3167 | 7.8531  |
| 0.4315        | 19.0  | 2622 | 0.4319          | 0.3185 | 8.0163  |
| 0.4315        | 20.0  | 2760 | 0.4316          | 0.318  | 8.0449  |
| 0.4315        | 21.0  | 2898 | 0.4313          | 0.3171 | 8.0571  |
| 0.4289        | 22.0  | 3036 | 0.4311          | 0.3195 | 7.9837  |
| 0.4289        | 23.0  | 3174 | 0.4308          | 0.3188 | 8.049   |
| 0.4289        | 24.0  | 3312 | 0.4307          | 0.3048 | 8.0694  |
| 0.4289        | 25.0  | 3450 | 0.4304          | 0.3046 | 8.1306  |
| 0.4264        | 26.0  | 3588 | 0.4303          | 0.3041 | 8.1224  |
| 0.4264        | 27.0  | 3726 | 0.4302          | 0.3044 | 8.1592  |
| 0.4264        | 28.0  | 3864 | 0.4301          | 0.3046 | 8.1306  |
| 0.4256        | 29.0  | 4002 | 0.4301          | 0.3039 | 8.1429  |
| 0.4256        | 30.0  | 4140 | 0.4301          | 0.3034 | 8.1551  |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0