transformers tensorboard safetensors t5 text2text-generation generated_from_trainer base_model:PRAli22/arat5-arabic-dialects-translation base_model:finetune:PRAli22/arat5-arabic-dialects-translation license:apache-2.0 autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: PRAli22/arat5-arabic-dialects-translation
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: t5-finetuned-ar-to-arsl_test_bleu
  results: []
---

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# t5-finetuned-ar-to-arsl_test_bleu

This model is a fine-tuned version of [PRAli22/arat5-arabic-dialects-translation](https://huggingface.co/PRAli22/arat5-arabic-dialects-translation) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3564
- Bleu1: 0.9326
- Bleu2: 0.9010
- Bleu3: 0.7310
- Bleu4: 0.5945
- Overall Bleu: 0.7773

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu1  | Bleu2  | Bleu3  | Bleu4  | Overall Bleu |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:------------:|
| No log        | 1.0   | 69   | 0.3152          | 0.9226 | 0.8885 | 0.7160 | 0.5780 | 0.7632       |
| No log        | 2.0   | 138  | 0.2849          | 0.9285 | 0.8941 | 0.7237 | 0.5864 | 0.7704       |
| No log        | 3.0   | 207  | 0.3064          | 0.9311 | 0.8992 | 0.7285 | 0.5913 | 0.7750       |
| No log        | 4.0   | 276  | 0.2908          | 0.9326 | 0.8984 | 0.7290 | 0.5914 | 0.7753       |
| No log        | 5.0   | 345  | 0.3007          | 0.9354 | 0.9034 | 0.7352 | 0.5975 | 0.7805       |
| No log        | 6.0   | 414  | 0.3043          | 0.9315 | 0.8991 | 0.7311 | 0.5940 | 0.7766       |
| No log        | 7.0   | 483  | 0.3124          | 0.9311 | 0.8981 | 0.7297 | 0.5941 | 0.7760       |
| 0.1232        | 8.0   | 552  | 0.3217          | 0.9302 | 0.8968 | 0.7254 | 0.5889 | 0.7726       |
| 0.1232        | 9.0   | 621  | 0.3201          | 0.9316 | 0.8989 | 0.7293 | 0.5946 | 0.7763       |
| 0.1232        | 10.0  | 690  | 0.3370          | 0.9317 | 0.8974 | 0.7280 | 0.5932 | 0.7752       |
| 0.1232        | 11.0  | 759  | 0.3458          | 0.9335 | 0.9013 | 0.7317 | 0.5954 | 0.7781       |
| 0.1232        | 12.0  | 828  | 0.3446          | 0.9324 | 0.8993 | 0.7291 | 0.5924 | 0.7758       |
| 0.1232        | 13.0  | 897  | 0.3516          | 0.9337 | 0.9017 | 0.7304 | 0.5938 | 0.7774       |
| 0.1232        | 14.0  | 966  | 0.3570          | 0.9331 | 0.9014 | 0.7309 | 0.5942 | 0.7774       |
| 0.0507        | 15.0  | 1035 | 0.3564          | 0.9326 | 0.9010 | 0.7310 | 0.5945 | 0.7773       |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
