Update README.md

README.md

@@ -9,31 +9,6 @@ metrics:
 - recall
 - f1
 - accuracy
-model-index:
-- name: KPOETA/BERTO-LOS-MUCHACHOS-1
-  results:
-  - task:
-      name: Token Classification
-      type: token-classification
-    dataset:
-      name: conll2002
-      type: conll2002
-      config: es
-      split: validation
-      args: es
-    metrics:
-    - name: Precision
-      type: precision
-      value: 0.880600409370025
-    - name: Recall
-      type: recall
-      value: 0.8897058823529411
-    - name: F1
-      type: f1
-      value: 0.8851297291118985
-    - name: Accuracy
-      type: accuracy
-      value: 0.9806463992982264
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -41,14 +16,38 @@ should probably proofread and complete it, then remove this comment. -->
 
 # xml-roberta-large-finetuned-ner
 
-Este es modelo resultado de un finetuning de 
-[FacebookAI/xlm-roberta-large-finetuned-conll03-english](https://huggingface.co/FacebookAI/xlm-roberta-large-finetuned-conll03-english) sobre el conll2002 dataset.
+
 Los siguientes son los resultados sobre el conjunto de evaluación:
-- Loss: 0.092
-- Precision: 0.8768651513038626
-- Recall: 0.8833942118572633
-- F1: 0.8768651513038628
-- Accuracy: 0.982701988941157
+{'eval_loss': 0.0929097980260849,
+ 'eval_precision': 0.8704318936877077,
+ 'eval_recall': 0.8833942118572633,
+ 'eval_f1': 0.8768651513038628,
+ 'eval_accuracy': 0.982701988941157,
+ 
+ 'eval_LOC': {'precision': 0.8867924528301887,
+  'recall': 0.8238007380073801,
+  'f1': 0.8541367766618843,
+  'number': 1084},
+  
+ 'eval_MISC': {'precision': 0.7349726775956285,
+  'recall': 0.7911764705882353,
+  'f1': 0.7620396600566574,
+  'number': 340},
+  
+ 'eval_ORG': {'precision': 0.8400272294077604,
+  'recall': 0.8814285714285715,
+  'f1': 0.8602300453119553,
+  'number': 1400},
+  
+ 'eval_PER': {'precision': 0.9599465954606141,
+  'recall': 0.9782312925170068,
+  'f1': 0.9690026954177898,
+  'number': 735},
+  
+ 'eval_runtime': 3.6357,
+ 'eval_samples_per_second': 417.526,
+ 'eval_steps_per_second': 26.13,
+ 'epoch': 5.0}
 
 ## Model description
 
@@ -65,13 +64,3 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - num_epochs: 5
-
-### Training results
-
-| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
-|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.0743        | 1.0   | 2081  | 0.1131          | 0.8385    | 0.8587 | 0.8485 | 0.9771   |
-| 0.049         | 2.0   | 4162  | 0.1429          | 0.8492    | 0.8564 | 0.8528 | 0.9756   |
-| 0.031         | 3.0   | 6243  | 0.1298          | 0.8758    | 0.8817 | 0.8787 | 0.9800   |
-| 0.0185        | 4.0   | 8324  | 0.1279          | 0.8827    | 0.8890 | 0.8859 | 0.9808   |
-| 0.0125        | 5.0   | 10405 | 0.1364          | 0.8806    | 0.8897 | 0.8851 | 0.9806   |