End of training

README.md

@@ -8,7 +8,7 @@ datasets:
 metrics:
 - accuracy
 model-index:
-- name: roberta-base-bne-finetuned-amazon_reviews_multi
+- name: roberta-base-bne-finetuned-multi-sentiment
   results:
   - task:
       name: Text Classification
@@ -22,18 +22,18 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.6882716049382716
+      value: 0.7222222222222222
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# roberta-base-bne-finetuned-amazon_reviews_multi
+# roberta-base-bne-finetuned-multi-sentiment
 
 This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggingface.co/BSC-TeMU/roberta-base-bne) on the multilingual-sentiments dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6935
-- Accuracy: 0.6883
+- Loss: 0.7635
+- Accuracy: 0.7222
 
 ## Model description
 
@@ -64,8 +64,8 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.786         | 1.0   | 115  | 0.6998          | 0.6914   |
-| 0.474         | 2.0   | 230  | 0.6935          | 0.6883   |
+| 0.6192        | 1.0   | 115  | 0.6712          | 0.7099   |
+| 0.217         | 2.0   | 230  | 0.7635          | 0.7222   |
 
 
 ### Framework versions