update model card README.md

README.md

@@ -1,5 +1,4 @@
 ---
-license: apache-2.0
 tags:
 - generated_from_trainer
 metrics:
@@ -17,13 +16,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # DistilBERTFINAL_ctxSentence_TRAIN_webDiscourse_TEST_NULL_second_train_set_null_False
 
-This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
+This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base](https://huggingface.co/cardiffnlp/twitter-roberta-base) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.5218
-- Precision: 0.9570
-- Recall: 0.0388
-- F1: 0.0745
-- Accuracy: 0.0651
+- Loss: 3.2555
+- Precision: 1.0
+- Recall: 0.0200
+- F1: 0.0393
+- Accuracy: 0.0486
 
 ## Model description
 
@@ -54,11 +53,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 95   | 0.5566          | 0.4167    | 0.1042 | 0.1667 | 0.75     |
-| No log        | 2.0   | 190  | 0.5253          | 0.5294    | 0.1875 | 0.2769 | 0.765    |
-| No log        | 3.0   | 285  | 0.5462          | 0.3947    | 0.3125 | 0.3488 | 0.72     |
-| No log        | 4.0   | 380  | 0.5591          | 0.3913    | 0.375  | 0.3830 | 0.71     |
-| No log        | 5.0   | 475  | 0.5559          | 0.4       | 0.2917 | 0.3373 | 0.725    |
+| No log        | 1.0   | 95   | 0.5756          | nan       | 0.0    | nan    | 0.715    |
+| No log        | 2.0   | 190  | 0.5340          | 0.6429    | 0.1579 | 0.2535 | 0.735    |
+| No log        | 3.0   | 285  | 0.5298          | 0.5833    | 0.3684 | 0.4516 | 0.745    |
+| No log        | 4.0   | 380  | 0.5325          | 0.5789    | 0.3860 | 0.4632 | 0.745    |
+| No log        | 5.0   | 475  | 0.5452          | 0.4815    | 0.4561 | 0.4685 | 0.705    |
 
 
 ### Framework versions