Translation
Transformers
TensorBoard
Safetensors
m2m_100
text2text-generation
Generated from Trainer
Instructions to use Mamadou2727/Feriji_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mamadou2727/Feriji_model 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="Mamadou2727/Feriji_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Mamadou2727/Feriji_model") model = AutoModelForSeq2SeqLM.from_pretrained("Mamadou2727/Feriji_model") - Notebooks
- Google Colab
- Kaggle
m2m100_418M-fr
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: 1.1488
- Bleu: 30.0608
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|---|---|---|---|---|
| 1.5114 | 1.0 | 14862 | 1.3923 | 24.3656 |
| 1.2359 | 2.0 | 29724 | 1.2308 | 27.5691 |
| 1.019 | 3.0 | 44586 | 1.1603 | 29.4766 |
| 0.8197 | 4.0 | 59448 | 1.1488 | 30.0608 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1
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Model tree for Mamadou2727/Feriji_model
Base model
facebook/m2m100_418M