Translation
Transformers
TensorFlow
Finnish
Swedish
marian
text2text-generation
generated_from_keras_callback
Instructions to use ossib/kho-v2-lex-fi-sv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ossib/kho-v2-lex-fi-sv 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="ossib/kho-v2-lex-fi-sv")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ossib/kho-v2-lex-fi-sv") model = AutoModelForSeq2SeqLM.from_pretrained("ossib/kho-v2-lex-fi-sv") - Notebooks
- Google Colab
- Kaggle
ossib/kho-v2-lex-fi-sv
This model is a fine-tuned version of Helsinki-NLP/opus-mt-fi-sv on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.7801
- Validation Loss: 0.9411
- Epoch: 2
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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 2727, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: mixed_float16
Training results
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 1.1488 | 0.9713 | 0 |
| 0.8948 | 0.9464 | 1 |
| 0.7801 | 0.9411 | 2 |
Framework versions
- Transformers 4.28.1
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3
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