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
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# t5-finetuned-ar-to-arsl_test

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: 0.3309
- Bleu1: 0.9310
- Bleu2: 0.8974
- Bleu3: 0.7219
- Bleu4: 0.5884

## 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  |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|
| No log        | 1.0   | 59   | 0.4660          | 0.8440 | 0.7803 | 0.5955 | 0.4626 |
| No log        | 2.0   | 118  | 0.3223          | 0.8966 | 0.8500 | 0.6689 | 0.5321 |
| No log        | 2.99  | 177  | 0.3004          | 0.9170 | 0.8791 | 0.7022 | 0.5644 |
| No log        | 3.99  | 236  | 0.2925          | 0.9205 | 0.8834 | 0.7071 | 0.5703 |
| No log        | 4.99  | 295  | 0.3099          | 0.9223 | 0.8859 | 0.7090 | 0.5716 |
| No log        | 5.99  | 354  | 0.2879          | 0.9244 | 0.8892 | 0.7125 | 0.5768 |
| No log        | 6.99  | 413  | 0.2971          | 0.9280 | 0.8936 | 0.7176 | 0.5824 |
| No log        | 8.0   | 473  | 0.2986          | 0.9254 | 0.8899 | 0.7136 | 0.5800 |
| 0.3874        | 9.0   | 532  | 0.3128          | 0.9293 | 0.8952 | 0.7204 | 0.5874 |
| 0.3874        | 10.0  | 591  | 0.3166          | 0.9316 | 0.8992 | 0.7242 | 0.5907 |
| 0.3874        | 10.99 | 650  | 0.3270          | 0.9303 | 0.8964 | 0.7214 | 0.5861 |
| 0.3874        | 11.99 | 709  | 0.3290          | 0.9304 | 0.8961 | 0.7223 | 0.5883 |
| 0.3874        | 12.99 | 768  | 0.3326          | 0.9296 | 0.8957 | 0.7216 | 0.5880 |
| 0.3874        | 13.99 | 827  | 0.3309          | 0.9294 | 0.8959 | 0.7208 | 0.5870 |
| 0.3874        | 14.97 | 885  | 0.3309          | 0.9310 | 0.8974 | 0.7219 | 0.5884 |


### Framework versions

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