first NLP model with hugging face done

README.md

@@ -2,12 +2,32 @@
 license: apache-2.0
 base_model: distilroberta-base
 tags:
+- text-classification
 - generated_from_trainer
 datasets:
 - glue
+metrics:
+- accuracy
+- f1
 model-index:
 - name: platzi-distilroberta-base-mrpc-glue-eloi-campeny
-  results: []
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: glue
+      type: glue
+      config: mrpc
+      split: validation
+      args: mrpc
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8382352941176471
+    - name: F1
+      type: f1
+      value: 0.8850174216027874
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -15,7 +35,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 # platzi-distilroberta-base-mrpc-glue-eloi-campeny
 
-This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the glue dataset.
+This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the glue and the mrpc datasets.
+It achieves the following results on the evaluation set:
+- Loss: 0.3864
+- Accuracy: 0.8382
+- F1: 0.8850
 
 ## Model description
 

all_results.json

@@ -1,14 +1,14 @@
 {
     "epoch": 1.0,
-    "eval_accuracy": 0.803921568627451,
-    "eval_f1": 0.8576512455516014,
-    "eval_loss": 0.40514302253723145,
-    "eval_runtime": 10.983,
-    "eval_samples_per_second": 37.148,
-    "eval_steps_per_second": 4.644,
+    "eval_accuracy": 0.8382352941176471,
+    "eval_f1": 0.8850174216027874,
+    "eval_loss": 0.3864043354988098,
+    "eval_runtime": 11.3745,
+    "eval_samples_per_second": 35.87,
+    "eval_steps_per_second": 4.484,
     "total_flos": 68399748276336.0,
-    "train_loss": 0.5326238229124115,
-    "train_runtime": 469.4311,
-    "train_samples_per_second": 7.814,
-    "train_steps_per_second": 0.978
+    "train_loss": 0.4123320070486962,
+    "train_runtime": 491.5347,
+    "train_samples_per_second": 7.462,
+    "train_steps_per_second": 0.934
 }

eval_results.json

@@ -1,9 +1,9 @@
 {
     "epoch": 1.0,
-    "eval_accuracy": 0.803921568627451,
-    "eval_f1": 0.8576512455516014,
-    "eval_loss": 0.40514302253723145,
-    "eval_runtime": 10.983,
-    "eval_samples_per_second": 37.148,
-    "eval_steps_per_second": 4.644
+    "eval_accuracy": 0.8382352941176471,
+    "eval_f1": 0.8850174216027874,
+    "eval_loss": 0.3864043354988098,
+    "eval_runtime": 11.3745,
+    "eval_samples_per_second": 35.87,
+    "eval_steps_per_second": 4.484
 }

train_results.json

@@ -1,8 +1,8 @@
 {
     "epoch": 1.0,
     "total_flos": 68399748276336.0,
-    "train_loss": 0.5326238229124115,
-    "train_runtime": 469.4311,
-    "train_samples_per_second": 7.814,
-    "train_steps_per_second": 0.978
+    "train_loss": 0.4123320070486962,
+    "train_runtime": 491.5347,
+    "train_samples_per_second": 7.462,
+    "train_steps_per_second": 0.934
 }