Bert_v11

This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-uncased on the None dataset. It achieves the following results on the evaluation set:

• eval_accuracy: 0.9032
• eval_f1: 0.9017
• eval_precision: 0.9035
• eval_recall: 0.9020
• eval_loss: 0.4575
• eval_runtime: 125.7967
• eval_samples_per_second: 30.048
• eval_steps_per_second: 0.946
• epoch: 0.0725
• step: 20

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: 3e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 200
• num_epochs: 15

Framework versions

• Transformers 4.44.2
• Pytorch 2.5.0+cu121
• Datasets 3.1.0
• Tokenizers 0.19.1