---
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
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# lab1_finetuning

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-fr](https://huggingface.co/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