Instructions to use Shularp/ar2enCkptfromgendata_03 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shularp/ar2enCkptfromgendata_03 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="Shularp/ar2enCkptfromgendata_03")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Shularp/ar2enCkptfromgendata_03") model = AutoModelForSeq2SeqLM.from_pretrained("Shularp/ar2enCkptfromgendata_03") - Notebooks
- Google Colab
- Kaggle
ar2enCkptfromgendata_03
This model is a fine-tuned version of Shularp/ar2enCkptfromgendata_02 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8021
- Bleu: 54.7767
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|---|---|---|---|---|
| 0.1882 | 1.0 | 38 | 0.8021 | 54.7767 |
| 0.2384 | 2.0 | 76 | 0.8021 | 54.7767 |
| 0.2024 | 3.0 | 114 | 0.8021 | 54.7767 |
| 0.1823 | 4.0 | 152 | 0.8021 | 54.7767 |
| 0.2082 | 5.0 | 190 | 0.8021 | 54.7767 |
| 0.2366 | 6.0 | 228 | 0.8021 | 54.7767 |
| 0.2485 | 7.0 | 266 | 0.8021 | 54.7767 |
| 0.199 | 8.0 | 304 | 0.8021 | 54.7767 |
| 0.2307 | 9.0 | 342 | 0.8021 | 54.7767 |
| 0.2629 | 10.0 | 380 | 0.8021 | 54.7767 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Downloads last month
- 7