Transformers
TensorBoard
Safetensors
mbart
text2text-generation
traduction
Generated from Trainer
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Instructions to use valintea/mbart-traduction-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use valintea/mbart-traduction-2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("valintea/mbart-traduction-2") model = AutoModelForSeq2SeqLM.from_pretrained("valintea/mbart-traduction-2") - Notebooks
- Google Colab
- Kaggle
mbart-traduction-2
This model is a fine-tuned version of facebook/mbart-large-50 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.5284
- Bleu: 4.1841
- Gen Len: 30.0483
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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| No log | 1.0 | 375 | 2.8734 | 1.211 | 40.9267 |
| 3.5795 | 2.0 | 750 | 2.5284 | 4.1841 | 30.0483 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Base model
facebook/mbart-large-50