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raulgdp/
beto-tass-finetuned-2026

Name: beto-tass-finetuned-2026
Availability: InStock

generated_from_trainer

dccuchile/bert-base-spanish-wwm-cased

finetune

text-embeddings-inference

endpoints_compatible

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Beto-tass-finetuned-2026

This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.2705
F1 Macro: 0.6360
F1 Weighted: 0.6409
Accuracy: 0.6410

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: 1e-05
train_batch_size: 16
eval_batch_size: 32
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Macro	F1 Weighted	Accuracy
0.9166	1.0	241	0.8403	0.6170	0.6204	0.6223
0.7287	2.0	482	0.8094	0.6498	0.6504	0.6504
0.5266	3.0	723	0.8743	0.6315	0.6373	0.6431
0.3562	4.0	964	1.0435	0.6284	0.6303	0.6243
0.2187	5.0	1205	1.2705	0.6360	0.6409	0.6410

Framework versions

Transformers 4.57.1
Pytorch 2.7.1+cu118
Datasets 4.2.0
Tokenizers 0.22.1

raulgdp/beto-tass-finetuned-2026

Beto-tass-finetuned-2026

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

raulgdp/
beto-tass-finetuned-2026