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Oscaroso28/
BETO_16

Name: BETO_16
Availability: InStock

generated_from_trainer

dccuchile/bert-base-spanish-wwm-cased

finetune

endpoints_compatible

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BETO_16

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

Loss: 0.0316
Precision: 0.9621
Recall: 0.9640
F1: 0.9631
Accuracy: 0.9939

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: 32
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 0.1
num_epochs: 8
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	195	0.1159	0.8592	0.8570	0.8581	0.9713
No log	2.0	390	0.0379	0.9485	0.9411	0.9448	0.9911
0.4583	3.0	585	0.0250	0.9601	0.9644	0.9622	0.9941
0.4583	4.0	780	0.0258	0.9772	0.9709	0.9740	0.9951
0.4583	5.0	975	0.0231	0.9781	0.9806	0.9793	0.9960
0.0273	6.0	1170	0.0227	0.9837	0.9780	0.9809	0.9962
0.0273	7.0	1365	0.0231	0.9831	0.9786	0.9809	0.9964
0.0123	8.0	1560	0.0232	0.9831	0.9793	0.9812	0.9964

Framework versions

Transformers 5.12.1
Pytorch 2.11.0+cu128
Datasets 5.0.0
Tokenizers 0.22.2

Oscaroso28/BETO_16

BETO_16

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Oscaroso28/
BETO_16