metadata
library_name: transformers
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-en-fr
tags:
- generated_from_trainer
datasets:
- kde4
metrics:
- bleu
model-index:
- name: lab1_finetuning
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: kde4
type: kde4
config: en-fr
split: train
args: en-fr
metrics:
- name: Bleu
type: bleu
value: 48.8947659869222
lab1_finetuning
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-fr on the kde4 dataset. It achieves the following results on the evaluation set:
- Loss: 1.0255
- Model Preparation Time: 0.0056
- Bleu: 48.8948
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: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Bleu |
|---|---|---|---|---|---|
| 1.4007 | 0.0476 | 500 | 1.2424 | 0.0056 | 45.5942 |
| 1.1468 | 0.0952 | 1000 | 1.1651 | 0.0056 | 46.9449 |
| 1.0415 | 0.1427 | 1500 | 1.1203 | 0.0056 | 47.6958 |
| 1.1744 | 0.1903 | 2000 | 1.0877 | 0.0056 | 44.0503 |
| 1.1876 | 0.2379 | 2500 | 1.0665 | 0.0056 | 48.6443 |
| 1.1702 | 0.2855 | 3000 | 1.0510 | 0.0056 | 47.1173 |
| 1.0369 | 0.3330 | 3500 | 1.0385 | 0.0056 | 48.8846 |
| 1.1668 | 0.3806 | 4000 | 1.0325 | 0.0056 | 49.0365 |
| 1.1351 | 0.4282 | 4500 | 1.0279 | 0.0056 | 48.8962 |
| 1.0436 | 0.4758 | 5000 | 1.0255 | 0.0056 | 49.0433 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.10.0+cu128
- Datasets 3.6.0
- Tokenizers 0.22.2