---
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: 1.1428
- Wer: 0.2368
- Cer: 0.0611
- Bleu: 59.1856

## 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: 64
- eval_batch_size: 64
- 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:-------:|
| 0.1721        | 1.0   | 1421  | 1.0128          | 0.2445 | 0.0640 | 58.5313 |
| 0.3157        | 2.0   | 2842  | 0.9088          | 0.2409 | 0.0625 | 59.1274 |
| 0.1958        | 3.0   | 4263  | 0.9950          | 0.2474 | 0.0617 | 58.7017 |
| 0.2275        | 4.0   | 5684  | 1.0075          | 0.2522 | 0.0638 | 58.2146 |
| 0.1139        | 5.0   | 7105  | 1.0297          | 0.2411 | 0.0607 | 59.7241 |
| 0.1243        | 6.0   | 8526  | 1.0343          | 0.2360 | 0.0608 | 59.9537 |
| 0.18          | 7.0   | 9947  | 1.0373          | 0.2423 | 0.0617 | 59.0538 |
| 0.1281        | 8.0   | 11368 | 1.1003          | 0.2344 | 0.0605 | 59.8118 |
| 0.1276        | 9.0   | 12789 | 1.1061          | 0.2385 | 0.0611 | 59.1765 |
| 0.1128        | 10.0  | 14210 | 1.1428          | 0.2368 | 0.0611 | 59.1856 |


### Framework versions

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