anger_frustration_detection_5

README.md

@@ -1,6 +1,7 @@
 ---
 library_name: transformers
-base_model: procit011/anger_frustration_detection_2
+license: mit
+base_model: pdelobelle/robbert-v2-dutch-base
 tags:
 - generated_from_trainer
 metrics:
@@ -16,11 +17,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 # results
 
-This model is a fine-tuned version of [procit011/anger_frustration_detection_2](https://huggingface.co/procit011/anger_frustration_detection_2) on the None dataset.
+This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-base](https://huggingface.co/pdelobelle/robbert-v2-dutch-base) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0457
-- F1: 0.9937
-- Accuracy: 0.9940
+- Loss: 0.0818
+- F1: 0.9886
+- Accuracy: 0.9891
 
 ## Model description
 
@@ -52,9 +53,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
-| 0.0822        | 1.0   | 829  | 0.0489          | 0.9911 | 0.9915   |
-| 0.0011        | 2.0   | 1658 | 0.0219          | 0.9962 | 0.9964   |
-| 0.0263        | 3.0   | 2487 | 0.0425          | 0.9949 | 0.9952   |
+| 0.0729        | 1.0   | 829  | 0.0889          | 0.9836 | 0.9843   |
+| 0.0331        | 2.0   | 1658 | 0.0319          | 0.9873 | 0.9879   |
+| 0.0001        | 3.0   | 2487 | 0.0392          | 0.9937 | 0.9940   |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:eb6e35c44dc705c9c4c1693392437267313469509fd94cb8ddea30ff2a7767e7
+oid sha256:576eb1283b28f21744786aced0611d08b893790cb7d187a53c3ee0beac46f222
 size 467078720