Model save

README.md

@@ -11,7 +11,6 @@ metrics:
 model-index:
 - name: test-NERv3
   results: []
-pipeline_tag: token-classification
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -21,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.1844
-- Precision: 0.0036
-- Recall: 0.0205
-- F1: 0.0061
-- Accuracy: 0.0872
+- Loss: 2.1950
+- Precision: 0.0009
+- Recall: 0.0026
+- F1: 0.0014
+- Accuracy: 0.1510
 
 ## Model description
 
@@ -57,7 +56,7 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 2.199         | 1.0   | 14   | 2.1844          | 0.0036    | 0.0205 | 0.0061 | 0.0872   |
+| 2.2261        | 1.0   | 14   | 2.1950          | 0.0009    | 0.0026 | 0.0014 | 0.1510   |
 
 
 ### Framework versions
@@ -65,4 +64,4 @@ The following hyperparameters were used during training:
 - Transformers 4.34.0
 - Pytorch 2.0.1+cu117
 - Datasets 2.12.0
-- Tokenizers 0.14.1
+- Tokenizers 0.14.1