---
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: 1.6541
- Wer: 0.2404
- Cer: 0.0668
- Bleu: 54.5297

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|
| 0.0382        | 1.0   | 313  | 1.4979          | 0.2436 | 0.0667 | 55.2918 |
| 0.0411        | 2.0   | 626  | 1.5980          | 0.2419 | 0.0653 | 55.4560 |
| 0.0622        | 3.0   | 939  | 1.5221          | 0.2383 | 0.0683 | 55.5429 |
| 0.0505        | 4.0   | 1252 | 1.5719          | 0.2388 | 0.0662 | 55.6735 |
| 0.0517        | 5.0   | 1565 | 1.6251          | 0.2373 | 0.0666 | 55.7046 |
| 0.0396        | 6.0   | 1878 | 1.5978          | 0.2431 | 0.0680 | 54.5671 |
| 0.0512        | 7.0   | 2191 | 1.5677          | 0.2675 | 0.1019 | 54.3154 |
| 0.0655        | 8.0   | 2504 | 1.5891          | 0.2448 | 0.0676 | 54.6644 |
| 0.05          | 9.0   | 2817 | 1.5952          | 0.2470 | 0.0703 | 54.7796 |
| 0.0415        | 10.0  | 3130 | 1.6541          | 0.2404 | 0.0668 | 54.5297 |


### Framework versions

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