Transformers
TensorBoard
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use NeutrinoPit/fine-tuned-t5-arabic-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NeutrinoPit/fine-tuned-t5-arabic-small with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("NeutrinoPit/fine-tuned-t5-arabic-small") model = AutoModelForSeq2SeqLM.from_pretrained("NeutrinoPit/fine-tuned-t5-arabic-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
fine-tuned-t5-arabic-small
This model is a fine-tuned version of NeutrinoPit/fine-tuned-t5-arabic-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9451
- Bleu: 0.0
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|---|---|---|---|---|
| 2.4041 | 1.0 | 14088 | 2.0718 | 0.0 |
| 2.2525 | 2.0 | 28176 | 1.9727 | 0.0 |
| 2.1935 | 3.0 | 42264 | 1.9451 | 0.0 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0
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