---
base_model: Samuael/geez_t5-15k
tags:
- generated_from_trainer
metrics:
- wer
- bleu
model-index:
- name: geez_t5-15k
  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. -->

# geez_t5-15k

This model is a fine-tuned version of [Samuael/geez_t5-15k](https://huggingface.co/Samuael/geez_t5-15k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4822
- Wer: 0.2284
- Cer: 0.0780
- Bleu: 67.0096

## 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: 0.0002
- train_batch_size: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    | Bleu    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|
| 0.2496        | 1.0   | 313  | 0.3291          | 0.2456 | 0.1077 | 67.2734 |
| 0.2573        | 2.0   | 626  | 0.3445          | 0.2488 | 0.1114 | 67.1612 |
| 0.2368        | 3.0   | 939  | 0.3483          | 0.2075 | 0.0698 | 69.4248 |
| 0.1459        | 4.0   | 1252 | 0.3815          | 0.2212 | 0.0806 | 68.5281 |
| 0.1552        | 5.0   | 1565 | 0.4081          | 0.2372 | 0.0934 | 66.8604 |
| 0.1031        | 6.0   | 1878 | 0.4143          | 0.2084 | 0.0692 | 69.6668 |
| 0.1067        | 7.0   | 2191 | 0.4325          | 0.2305 | 0.0853 | 67.3479 |
| 0.1111        | 8.0   | 2504 | 0.4380          | 0.2070 | 0.0638 | 68.9579 |
| 0.0965        | 9.0   | 2817 | 0.4541          | 0.2195 | 0.0735 | 67.8519 |
| 0.0843        | 10.0  | 3130 | 0.4822          | 0.2284 | 0.0780 | 67.0096 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2