Training complete

README.md

@@ -1,6 +1,6 @@
 ---
 license: apache-2.0
-base_model: distilbert-base-uncased
+base_model: bert-base-cased
 tags:
 - generated_from_trainer
 metrics:
@@ -15,15 +15,15 @@ should probably proofread and complete it, then remove this comment. -->
 
 # bert-goemotions-15epochs-run2
 
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1106
-- Accuracy Thresh: 0.9619
-- F1 weighted: {'f1': 0.3982045872720165}
-- F1 macro: {'f1': 0.31538372135978}
-- Accuracy: {'accuracy': 0.4170647653000594}
-- Recall weighted: {'recall': 0.4170647653000594}
-- Recall macro: {'recall': 0.32808068442725}
+- Loss: 0.1154
+- Accuracy Thresh: 0.9616
+- F1 weighted: 0.3672
+- F1 macro: 0.2835
+- Accuracy: 0.4083
+- Recall weighted: 0.4083
+- Recall macro: 0.2851
 
 ## Model description
 
@@ -53,15 +53,16 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step  | Validation Loss | Accuracy Thresh | F1 weighted                 | F1 macro                    | Accuracy                          | Recall weighted                 | Recall macro                    |
-|:-------------:|:-----:|:-----:|:---------------:|:---------------:|:---------------------------:|:---------------------------:|:---------------------------------:|:-------------------------------:|:-------------------------------:|
-| 0.1259        | 1.0   | 5286  | 0.1127          | 0.9617          | {'f1': 0.3890983386624071}  | {'f1': 0.3007761920553838}  | {'accuracy': 0.41630421865715983} | {'recall': 0.41630421865715983} | {'recall': 0.3213896867494273}  |
-| 0.1102        | 2.0   | 10572 | 0.1106          | 0.9619          | {'f1': 0.3982045872720165}  | {'f1': 0.31538372135978}    | {'accuracy': 0.4170647653000594}  | {'recall': 0.4170647653000594}  | {'recall': 0.32808068442725}    |
-| 0.1052        | 3.0   | 15858 | 0.1107          | 0.9619          | {'f1': 0.3980887152485667}  | {'f1': 0.3181332487636058}  | {'accuracy': 0.4168983957219251}  | {'recall': 0.4168983957219251}  | {'recall': 0.32790458379700677} |
-| 0.1008        | 4.0   | 21144 | 0.1117          | 0.9616          | {'f1': 0.39966069827702533} | {'f1': 0.32238147844285014} | {'accuracy': 0.4169459298871064}  | {'recall': 0.4169459298871064}  | {'recall': 0.3280426755048108}  |
-| 0.0968        | 5.0   | 26430 | 0.1138          | 0.9609          | {'f1': 0.39833587917024693} | {'f1': 0.32459673497912495} | {'accuracy': 0.4110516934046346}  | {'recall': 0.4110516934046346}  | {'recall': 0.3347612567297387}  |
-| 0.0934        | 6.0   | 31716 | 0.1158          | 0.9604          | {'f1': 0.3893454681480969}  | {'f1': 0.3185494353334119}  | {'accuracy': 0.39786096256684494} | {'recall': 0.39786096256684494} | {'recall': 0.3332642189610775}  |
-| 0.0902        | 7.0   | 37002 | 0.1188          | 0.9596          | {'f1': 0.3843621716402447}  | {'f1': 0.3127316237002698}  | {'accuracy': 0.39332144979203804} | {'recall': 0.39332144979203804} | {'recall': 0.32900959748461356} |
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy Thresh | F1 weighted | F1 macro | Accuracy | Recall weighted | Recall macro |
+|:-------------:|:-----:|:-----:|:---------------:|:---------------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|
+| 0.1322        | 1.0   | 5283  | 0.1205          | 0.9609          | 0.3371      | 0.2432   | 0.3944   | 0.3944          | 0.2539       |
+| 0.1189        | 2.0   | 10566 | 0.1165          | 0.9614          | 0.3573      | 0.2726   | 0.4062   | 0.4062          | 0.2835       |
+| 0.114         | 3.0   | 15849 | 0.1154          | 0.9616          | 0.3672      | 0.2835   | 0.4083   | 0.4083          | 0.2851       |
+| 0.1098        | 4.0   | 21132 | 0.1157          | 0.9613          | 0.3743      | 0.2929   | 0.4019   | 0.4019          | 0.2996       |
+| 0.1059        | 5.0   | 26415 | 0.1172          | 0.9609          | 0.3751      | 0.2959   | 0.4002   | 0.4002          | 0.3049       |
+| 0.1023        | 6.0   | 31698 | 0.1173          | 0.9610          | 0.3779      | 0.3012   | 0.3986   | 0.3986          | 0.3135       |
+| 0.0988        | 7.0   | 36981 | 0.1188          | 0.9603          | 0.3805      | 0.3082   | 0.3925   | 0.3925          | 0.3175       |
+| 0.0956        | 8.0   | 42264 | 0.1199          | 0.9601          | 0.3803      | 0.3044   | 0.3973   | 0.3973          | 0.3129       |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:50dd3780f2d290d23966a4191ad84b798cbc29c55ae3f00792a9259e5f0dd684
 size 433345360

runs/Nov15_03-23-21_b4e21ea9cd63/events.out.tfevents.1700021515.b4e21ea9cd63.3918.1

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9d4f4f0c18304ea659389ebd83047fd813ce6721aab26bafd7043c299cfb789b
+size 703