---
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
---

<!-- 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_random

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: 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