update model card README.md

README.md

@@ -1,10 +1,6 @@
 ---
-language:
-- es
 tags:
 - generated_from_trainer
-datasets:
-- jorgeortizfuentes/spanish_nominal_groups_conll2003
 model-index:
 - name: nominal-groups-recognition-bert-base-spanish-wwm-cased
   results: []
@@ -15,17 +11,17 @@ should probably proofread and complete it, then remove this comment. -->
 
 # nominal-groups-recognition-bert-base-spanish-wwm-cased
 
-This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on the jorgeortizfuentes/spanish_nominal_groups_conll2003 dataset.
+This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2988
-- Ng Precision: 0.7309
-- Ng Recall: 0.7780
-- Ng F1: 0.7537
+- Loss: 0.3568
+- Ng Precision: 0.7280
+- Ng Recall: 0.7767
+- Ng F1: 0.7516
 - Ng Number: 3198
-- Overall Precision: 0.7309
-- Overall Recall: 0.7780
-- Overall F1: 0.7537
-- Overall Accuracy: 0.9019
+- Overall Precision: 0.7280
+- Overall Recall: 0.7767
+- Overall F1: 0.7516
+- Overall Accuracy: 0.8992
 
 ## Model description
 
@@ -45,8 +41,8 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 16
-- eval_batch_size: 16
+- train_batch_size: 8
+- eval_batch_size: 8
 - seed: 13
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -56,16 +52,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Ng Precision | Ng Recall | Ng F1  | Ng Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:------------:|:---------:|:------:|:---------:|:-----------------:|:--------------:|:----------:|:----------------:|
-| 0.451         | 1.0   | 114  | 0.2882          | 0.6985       | 0.7483    | 0.7225 | 3198      | 0.6985            | 0.7483         | 0.7225     | 0.8899           |
-| 0.2429        | 2.0   | 228  | 0.2917          | 0.7294       | 0.7483    | 0.7387 | 3198      | 0.7294            | 0.7483         | 0.7387     | 0.8932           |
-| 0.193         | 3.0   | 342  | 0.2864          | 0.7306       | 0.7727    | 0.7511 | 3198      | 0.7306            | 0.7727         | 0.7511     | 0.9000           |
-| 0.1586        | 4.0   | 456  | 0.2988          | 0.7309       | 0.7780    | 0.7537 | 3198      | 0.7309            | 0.7780         | 0.7537     | 0.9019           |
-| 0.1386        | 5.0   | 570  | 0.3116          | 0.7275       | 0.7770    | 0.7514 | 3198      | 0.7275            | 0.7770         | 0.7514     | 0.9003           |
+| 0.3955        | 1.0   | 228  | 0.2778          | 0.7129       | 0.7492    | 0.7306 | 3198      | 0.7129            | 0.7492         | 0.7306     | 0.8924           |
+| 0.2186        | 2.0   | 456  | 0.2763          | 0.7318       | 0.7711    | 0.7509 | 3198      | 0.7318            | 0.7711         | 0.7509     | 0.8990           |
+| 0.1586        | 3.0   | 684  | 0.2960          | 0.7274       | 0.7733    | 0.7496 | 3198      | 0.7274            | 0.7733         | 0.7496     | 0.8992           |
+| 0.119         | 4.0   | 912  | 0.3330          | 0.7283       | 0.7727    | 0.7498 | 3198      | 0.7283            | 0.7727         | 0.7498     | 0.8982           |
+| 0.0943        | 5.0   | 1140 | 0.3568          | 0.7280       | 0.7767    | 0.7516 | 3198      | 0.7280            | 0.7767         | 0.7516     | 0.8992           |
 
 
 ### Framework versions
 
 - Transformers 4.30.2
-- Pytorch 2.0.1+cu117
+- Pytorch 2.0.1+cu118
 - Datasets 2.13.1
 - Tokenizers 0.13.3