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---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
datasets:
- opus_books
metrics:
- bleu
model-index:
- name: en-to-es-trans-with-bart
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: opus_books
type: opus_books
config: en-es
split: train
args: en-es
metrics:
- name: Bleu
type: bleu
value: 2.1888
---
<!-- 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. -->
# en-to-es-trans-with-bart
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on the opus_books dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0355
- Bleu: 2.1888
- Gen Len: 18.6278
## 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: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| 2.4648 | 1.0 | 4674 | 2.1509 | 1.937 | 18.6399 |
| 2.2417 | 2.0 | 9348 | 2.0355 | 2.1888 | 18.6278 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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