This model has been trained to translate texts from English to Spanish, specifically focused on environmental topics and green policies. Fine-tuning was done on a relatively small dataset, which makes the results variable depending on the complexity and context of the translation.

Training and evaluation data

The dataset is the following one: ClimateChangeMeasures

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5.6e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Gen Len
No log	1.0	28	3.5296	12.3925	26.1455
No log	2.0	56	3.4070	13.6296	28.6364

Framework versions

Transformers 4.50.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1

Irisba/mbart-ClimateChangeMeasures-en-es

mbart-ClimateChangeMeasures-en-es

Uses and limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Irisba/
mbart-ClimateChangeMeasures-en-es