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_random
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: 6.051969601236915
lab1_random
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: 5.2440
- Model Preparation Time: 0.0028
- Bleu: 6.0520
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 |
|---|---|---|---|---|---|
| 6.7996 | 0.0476 | 500 | 6.7513 | 0.0028 | 3.5511 |
| 6.1464 | 0.0952 | 1000 | 6.2017 | 0.0028 | 5.0638 |
| 5.927 | 0.1427 | 1500 | 5.9045 | 0.0028 | 5.1608 |
| 5.7975 | 0.1903 | 2000 | 5.6937 | 0.0028 | 5.1830 |
| 5.4751 | 0.2379 | 2500 | 5.5416 | 0.0028 | 4.7912 |
| 5.4717 | 0.2855 | 3000 | 5.4346 | 0.0028 | 6.3369 |
| 5.2174 | 0.3330 | 3500 | 5.3458 | 0.0028 | 4.9379 |
| 5.5536 | 0.3806 | 4000 | 5.2918 | 0.0028 | 5.7794 |
| 5.3342 | 0.4282 | 4500 | 5.2603 | 0.0028 | 6.3629 |
| 5.4492 | 0.4758 | 5000 | 5.2440 | 0.0028 | 6.0904 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.10.0+cu128
- Datasets 3.6.0
- Tokenizers 0.22.2