update model card README.md

README.md

@@ -1,11 +1,7 @@
 ---
-language:
-- es
 license: cc-by-nc-4.0
 tags:
 - generated_from_trainer
-datasets:
-- jpherrerap/competencia2
 model-index:
 - name: ner-roberta-es-clinical-trials-ner
   results: []
@@ -16,33 +12,33 @@ should probably proofread and complete it, then remove this comment. -->
 
 # ner-roberta-es-clinical-trials-ner
 
-This model is a fine-tuned version of [lcampillos/roberta-es-clinical-trials-ner](https://huggingface.co/lcampillos/roberta-es-clinical-trials-ner) on the jpherrerap/competencia2 dataset.
+This model is a fine-tuned version of [lcampillos/roberta-es-clinical-trials-ner](https://huggingface.co/lcampillos/roberta-es-clinical-trials-ner) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2811
-- Body Part Precision: 0.6861
-- Body Part Recall: 0.7766
-- Body Part F1: 0.7286
+- Loss: 0.2661
+- Body Part Precision: 0.7124
+- Body Part Recall: 0.8173
+- Body Part F1: 0.7612
 - Body Part Number: 197
-- Disease Precision: 0.7476
-- Disease Recall: 0.7505
-- Disease F1: 0.7490
+- Disease Precision: 0.7712
+- Disease Recall: 0.7697
+- Disease F1: 0.7704
 - Disease Number: 521
 - Family Member Precision: 0.8462
 - Family Member Recall: 0.8462
 - Family Member F1: 0.8462
 - Family Member Number: 13
-- Medication Precision: 0.8158
+- Medication Precision: 0.8378
 - Medication Recall: 0.8378
-- Medication F1: 0.8267
+- Medication F1: 0.8378
 - Medication Number: 37
-- Procedure Precision: 0.6282
-- Procedure Recall: 0.7313
-- Procedure F1: 0.6759
+- Procedure Precision: 0.6510
+- Procedure Recall: 0.7239
+- Procedure F1: 0.6855
 - Procedure Number: 134
-- Overall Precision: 0.7177
-- Overall Recall: 0.7583
-- Overall F1: 0.7375
-- Overall Accuracy: 0.9174
+- Overall Precision: 0.7418
+- Overall Recall: 0.7772
+- Overall F1: 0.7591
+- Overall Accuracy: 0.9238
 
 ## Model description
 
@@ -61,21 +57,20 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
+- learning_rate: 5e-05
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 13
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 3
+- num_epochs: 2
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Body Part Precision | Body Part Recall | Body Part F1 | Body Part Number | Disease Precision | Disease Recall | Disease F1 | Disease Number | Family Member Precision | Family Member Recall | Family Member F1 | Family Member Number | Medication Precision | Medication Recall | Medication F1 | Medication Number | Procedure Precision | Procedure Recall | Procedure F1 | Procedure Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:-------------------:|:----------------:|:------------:|:----------------:|:-----------------:|:--------------:|:----------:|:--------------:|:-----------------------:|:--------------------:|:----------------:|:--------------------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:-------------------:|:----------------:|:------------:|:----------------:|:-----------------:|:--------------:|:----------:|:----------------:|
-| 0.3951        | 1.0   | 502  | 0.2831          | 0.6697              | 0.7513           | 0.7081       | 197              | 0.7314            | 0.7370         | 0.7342     | 521            | 1.0                     | 0.8462               | 0.9167           | 13                   | 0.625                | 0.6757            | 0.6494        | 37                | 0.5556              | 0.6716           | 0.6081       | 134              | 0.6861            | 0.7295         | 0.7071     | 0.9144           |
-| 0.2123        | 2.0   | 1004 | 0.2912          | 0.6623              | 0.7665           | 0.7106       | 197              | 0.7389            | 0.7332         | 0.7360     | 521            | 0.7857                  | 0.8462               | 0.8148           | 13                   | 0.675                | 0.7297            | 0.7013        | 37                | 0.6289              | 0.7463           | 0.6826       | 134              | 0.7004            | 0.7439         | 0.7215     | 0.9132           |
-| 0.1686        | 3.0   | 1506 | 0.2811          | 0.6861              | 0.7766           | 0.7286       | 197              | 0.7476            | 0.7505         | 0.7490     | 521            | 0.8462                  | 0.8462               | 0.8462           | 13                   | 0.8158               | 0.8378            | 0.8267        | 37                | 0.6282              | 0.7313           | 0.6759       | 134              | 0.7177            | 0.7583         | 0.7375     | 0.9174           |
+| 0.3329        | 1.0   | 502  | 0.2561          | 0.6830              | 0.7766           | 0.7268       | 197              | 0.7718            | 0.7658         | 0.7688     | 521            | 0.9231                  | 0.9231               | 0.9231           | 13                   | 0.75                 | 0.8108            | 0.7792        | 37                | 0.6218              | 0.7239           | 0.6690       | 134              | 0.7274            | 0.7661         | 0.7462     | 0.9219           |
+| 0.1699        | 2.0   | 1004 | 0.2661          | 0.7124              | 0.8173           | 0.7612       | 197              | 0.7712            | 0.7697         | 0.7704     | 521            | 0.8462                  | 0.8462               | 0.8462           | 13                   | 0.8378               | 0.8378            | 0.8378        | 37                | 0.6510              | 0.7239           | 0.6855       | 134              | 0.7418            | 0.7772         | 0.7591     | 0.9238           |
 
 
 ### Framework versions