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---
library_name: transformers
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-ca-en
tags:
- translation
- generated_from_trainer
datasets:
- kde4
metrics:
- bleu
model-index:
- name: opus-mt-ca-en-ft-kde4-mt-ca-en
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: kde4
type: kde4
config: ca-en
split: train
args: ca-en
metrics:
- name: Bleu
type: bleu
value: 67.67792228946597
---
<!-- 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-ca-en-ft-kde4-mt-ca-en
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ca-en](https://huggingface.co/Helsinki-NLP/opus-mt-ca-en) on the kde4 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5999
- Model Preparation Time: 0.0033
- Bleu: 67.6779
## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1