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---
library_name: transformers
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: ft-t5-small-lg
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. -->
# ft-t5-small-lg
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the Luganda Formal Data dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2411
- Bleu: 1.4907
- Gen Len: 14.5428
## 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
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|
| 0.3208 | 1.0 | 2051 | 0.2999 | 0.0574 | 8.6396 |
| 0.3054 | 2.0 | 4102 | 0.2890 | 0.1846 | 8.7257 |
| 0.2954 | 3.0 | 6153 | 0.2820 | 0.2253 | 11.5285 |
| 0.2915 | 4.0 | 8204 | 0.2755 | 0.2485 | 11.8231 |
| 0.2841 | 5.0 | 10255 | 0.2706 | 0.1711 | 14.2913 |
| 0.2809 | 6.0 | 12306 | 0.2667 | 0.2453 | 14.0332 |
| 0.2758 | 7.0 | 14357 | 0.2635 | 0.3568 | 15.1871 |
| 0.2721 | 8.0 | 16408 | 0.2609 | 0.4433 | 15.1297 |
| 0.2683 | 9.0 | 18459 | 0.2586 | 0.5148 | 14.9026 |
| 0.2668 | 10.0 | 20510 | 0.2562 | 0.5717 | 14.9704 |
| 0.2658 | 11.0 | 22561 | 0.2546 | 0.6013 | 14.9334 |
| 0.2665 | 12.0 | 24612 | 0.2528 | 0.6211 | 14.7852 |
| 0.2611 | 13.0 | 26663 | 0.2512 | 0.6801 | 14.7521 |
| 0.2617 | 14.0 | 28714 | 0.2499 | 0.7704 | 14.8426 |
| 0.2589 | 15.0 | 30765 | 0.2486 | 0.846 | 14.7227 |
| 0.257 | 16.0 | 32816 | 0.2477 | 0.9404 | 14.6676 |
| 0.2552 | 17.0 | 34867 | 0.2466 | 0.8846 | 14.5691 |
| 0.2577 | 18.0 | 36918 | 0.2458 | 1.0307 | 14.6182 |
| 0.254 | 19.0 | 38969 | 0.2450 | 1.038 | 14.5272 |
| 0.2539 | 20.0 | 41020 | 0.2442 | 1.1301 | 14.5494 |
| 0.2524 | 21.0 | 43071 | 0.2436 | 1.1553 | 14.571 |
| 0.2555 | 22.0 | 45122 | 0.2429 | 1.2626 | 14.6193 |
| 0.2506 | 23.0 | 47173 | 0.2427 | 1.3183 | 14.5 |
| 0.2491 | 24.0 | 49224 | 0.2421 | 1.3981 | 14.5801 |
| 0.2499 | 25.0 | 51275 | 0.2419 | 1.4025 | 14.534 |
| 0.2482 | 26.0 | 53326 | 0.2415 | 1.404 | 14.5639 |
| 0.2479 | 27.0 | 55377 | 0.2414 | 1.4074 | 14.554 |
| 0.247 | 28.0 | 57428 | 0.2412 | 1.4902 | 14.542 |
| 0.2477 | 29.0 | 59479 | 0.2411 | 1.4932 | 14.5653 |
| 0.2477 | 30.0 | 61530 | 0.2411 | 1.4907 | 14.5428 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.0
- Tokenizers 0.19.1
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