Update README.md

README.md

@@ -18,36 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 
 Los siguientes son los resultados sobre el conjunto de evaluación:
-{'eval_loss': 0.0929097980260849,
- 'eval_precision': 0.8704318936877077,
- 'eval_recall': 0.8833942118572633,
- 'eval_f1': 0.8768651513038628,
- 'eval_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
 
@@ -57,10 +34,40 @@ con el fin de almacenar de manera temoporal el modelo que pesa alrededor de 35 G
 
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
-- train_batch_size: 4
-- eval_batch_size: 8
-- seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- num_epochs: 5
+    eval_strategy="epoch",
+    save_strategy="epoch",
+    learning_rate=2e-5, # (Aprendizaje se esta cambiando)
+    per_device_train_batch_size=16,
+    per_device_eval_batch_size=16,
+    num_train_epochs=5,
+    weight_decay=0.1,
+    max_grad_norm=1.0,
+    adam_epsilon=1e-5,
+    fp16=True,
+    save_total_limit=2,
+    load_best_model_at_end=True,
+    push_to_hub=True,
+    metric_for_best_model="f1",
+    seed=42,
+
+
+
+| Metric          | Value       |
+|-----------------|-------------|
+| eval_loss       | 0.12918254733085632 |
+| eval_precision  | 0.8674463937621832 |
+| eval_recall     | 0.8752458555774094 |
+| eval_f1         | 0.8713286713286713 |
+| eval_accuracy   | 0.9813980358174466 |
+| eval_runtime    | 3.6357      |
+| eval_samples_per_second | 417.526 |
+| eval_steps_per_second   | 26.13   |
+| epoch           | 5.0         |
+
+| Label  | Precision | Recall | F1        | Number |
+|--------|-----------|--------|------------|--------|
+| LOC    | 0.8867924528301887 | 0.8238007380073801 | 0.8541367766618843 | 1084 |
+| MISC   | 0.7349726775956285 | 0.7911764705882353 | 0.7620396600566574 | 340  |
+| ORG    | 0.8400272294077604 | 0.8814285714285715 | 0.8602300453119553 | 1400 |
+| PER    | 0.9599465954606141 | 0.9782312925170068 | 0.9690026954177898 | 735  |
+