exp1_10partition_modeloorig

This model is a fine-tuned version of Helsinki-NLP/opus-mt-es-es on the None dataset. It achieves the following results on the evaluation set:

• eval_loss: 1.4402
• eval_model_preparation_time: 0.0032
• eval_bleu_msl: 100.0000
• eval_bleu_1_msl: 0.44
• eval_bleu_2_msl: 0.0121
• eval_bleu_3_msl: 0.0039
• eval_bleu_4_msl: 0.0020
• eval_ter_msl: 100
• eval_bleu_asl: 0
• eval_bleu_1_asl: 0
• eval_bleu_2_asl: 0
• eval_bleu_3_asl: 0
• eval_bleu_4_asl: 0
• eval_ter_asl: 100
• eval_runtime: 6.2009
• eval_samples_per_second: 48.38
• eval_steps_per_second: 0.806
• step: 0

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: 0.0001
• train_batch_size: 32
• eval_batch_size: 64
• 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: 30
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.49.0
• Pytorch 2.5.1+cu124
• Datasets 3.3.2
• Tokenizers 0.21.0