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raulgdp/
sentiment-BETO-es-2025_II

Name: sentiment-BETO-es-2025_II
Availability: InStock

generated_from_trainer

finiteautomata/beto-sentiment-analysis

finetune

text-embeddings-inference

endpoints_compatible

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sentiment-BETO-es-2025_II

This model is a fine-tuned version of finiteautomata/beto-sentiment-analysis on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.3492
F1 Macro: 0.6581
F1 Weighted: 0.6599
Accuracy: 0.6562

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: 16
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_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Macro	F1 Weighted	Accuracy
0.053	1.0	241	0.0462	0.9868	0.9865	0.9865
0.0416	2.0	482	0.0287	0.9957	0.9958	0.9958
0.0252	3.0	723	0.0293	0.9936	0.9938	0.9938
0.0133	4.0	964	0.0296	0.9906	0.9906	0.9906
0.0083	5.0	1205	0.0469	0.9926	0.9927	0.9927

Framework versions

Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1

raulgdp/sentiment-BETO-es-2025_II

sentiment-BETO-es-2025_II

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

raulgdp/
sentiment-BETO-es-2025_II