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This model is a fine-tuned version of facebook/m2m100_418M on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1653
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: 5e-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
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.8064 | 0.2 | 100 | 0.4321 |
| 0.3145 | 0.41 | 200 | 0.2218 |
| 0.2633 | 0.61 | 300 | 0.1970 |
| 0.2428 | 0.81 | 400 | 0.1871 |
| 0.2162 | 1.02 | 500 | 0.1786 |
| 0.163 | 1.22 | 600 | 0.1744 |
| 0.1515 | 1.42 | 700 | 0.1713 |
| 0.1423 | 1.63 | 800 | 0.1696 |
| 0.1439 | 1.83 | 900 | 0.1660 |
| 0.1484 | 2.03 | 1000 | 0.1653 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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facebook/m2m100_418M
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Ragab167/output") model = AutoModelForSeq2SeqLM.from_pretrained("Ragab167/output")