consejo-ner

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

• Loss: 0.3066
• Precision: 0.7241
• Recall: 0.6774
• F1: 0.7
• Accuracy: 0.9313

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: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	15	1.5724	0.0	0.0	0.0	0.6985
No log	2.0	30	1.3540	0.0	0.0	0.0	0.6985
No log	3.0	45	1.0972	0.0	0.0	0.0	0.7099
No log	4.0	60	0.8615	0.5833	0.2258	0.3256	0.7672
No log	5.0	75	0.7381	0.5	0.3548	0.4151	0.8244
No log	6.0	90	0.6111	0.5556	0.4839	0.5172	0.8473
No log	7.0	105	0.5353	0.5185	0.4516	0.4828	0.8550
No log	8.0	120	0.4786	0.5769	0.4839	0.5263	0.8626
No log	9.0	135	0.4493	0.5357	0.4839	0.5085	0.8817
No log	10.0	150	0.4269	0.4839	0.4839	0.4839	0.8779
No log	11.0	165	0.3977	0.5938	0.6129	0.6032	0.8931
No log	12.0	180	0.3669	0.5161	0.5161	0.5161	0.8969
No log	13.0	195	0.3437	0.6786	0.6129	0.6441	0.9237
No log	14.0	210	0.3389	0.6786	0.6129	0.6441	0.9198
No log	15.0	225	0.3249	0.6786	0.6129	0.6441	0.9198
No log	16.0	240	0.3102	0.6897	0.6452	0.6667	0.9275
No log	17.0	255	0.3094	0.6667	0.6452	0.6557	0.9275
No log	18.0	270	0.3159	0.7	0.6774	0.6885	0.9198
No log	19.0	285	0.3094	0.7241	0.6774	0.7	0.9313
No log	20.0	300	0.3066	0.7241	0.6774	0.7	0.9313

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu116
• Datasets 2.9.0
• Tokenizers 0.13.2