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---
license: apache-2.0
base_model: DevAibest/opus-mt-finetuned-en-to-fr
tags:
- generated_from_trainer
datasets:
- opus_books
metrics:
- bleu
model-index:
- name: opus-mt-finetuned-en-to-fr
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: opus_books
type: opus_books
config: en-fr
split: train
args: en-fr
metrics:
- name: Bleu
type: bleu
value: 69.4791
---
<!-- 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. -->
# opus-mt-finetuned-en-to-fr
This model is a fine-tuned version of [DevAibest/opus-mt-finetuned-en-to-fr](https://huggingface.co/DevAibest/opus-mt-finetuned-en-to-fr) on the opus_books dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2610
- Bleu: 69.4791
- Gen Len: 32.7639
## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.4587 | 1.0 | 6355 | 0.2063 | 76.6735 | 32.6691 |
| 0.426 | 2.0 | 12710 | 0.2238 | 74.291 | 32.7606 |
| 0.3935 | 3.0 | 19065 | 0.2385 | 72.4894 | 32.8613 |
| 0.3723 | 4.0 | 25420 | 0.2480 | 71.2701 | 32.635 |
| 0.3492 | 5.0 | 31775 | 0.2532 | 70.6417 | 32.7086 |
| 0.3315 | 6.0 | 38130 | 0.2588 | 69.8185 | 32.7439 |
| 0.3057 | 7.0 | 44485 | 0.2598 | 69.7941 | 32.7479 |
| 0.2906 | 8.0 | 50840 | 0.2621 | 69.5144 | 32.7624 |
| 0.283 | 9.0 | 57195 | 0.2619 | 69.27 | 32.7373 |
| 0.2675 | 10.0 | 63550 | 0.2610 | 69.4791 | 32.7639 |
### Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
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