Update README.md

README.md

@@ -7,29 +7,28 @@ metrics:
 model-index:
 - name: ruBert-base-russian-emotions-classifier-goEmotions
   results: []
+datasets:
+- Djacon/ru_goemotions
+language:
+- ru
 ---
 
-<!-- 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. -->
 
 # ruBert-base-russian-emotions-classifier-goEmotions
 
-This model is a fine-tuned version of [ai-forever/ruBert-base](https://huggingface.co/ai-forever/ruBert-base) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.2606
-- Accuracy: 0.8950
+This model is a fine-tuned version of [ai-forever/ruBert-base](https://huggingface.co/ai-forever/ruBert-base) on [Djacon/ru_goemotions](https://huggingface.co/datasets/Djacon/ru_goemotions).
+It achieves the following results on the evaluation set (2nd epoch):
+- Loss: 0.2088
+- AUC: 0.9240
 
-## Model description
+The quality of the predicted probabilities on the test dataset is the following:
 
-More information needed
+| label    | joy    | interest | surpise | sadness | anger  | disgust | fear   | guilt  | neutral | average |
+|----------|--------|----------|---------|---------|--------|---------|--------|--------|---------|---------|
+| AUC      | 0.9369 | 0.9213   | 0.9325  | 0.8791  | 0.8374 | 0.9041  | 0.9470 | 0.9758 | 0.8518  | 0.9095  |
+| F1-micro | 0.9528 | 0.9157   | 0.9697  | 0.9284  | 0.8690 | 0.9658  | 0.9851 | 0.9875 | 0.7654  | 0.9266  |
+| F1-macro | 0.8369 | 0.7922   | 0.7561  | 0.7392  | 0.7351 | 0.7356  | 0.8176 | 0.8247 | 0.7650  | 0.7781  |
 
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
 
 ## Training procedure
 
@@ -42,17 +41,15 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 5
+- num_epochs: 3
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+| Training Loss | Epoch | Step | Validation Loss | AUC      |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
 | 0.1755        | 1.0   | 1685 | 0.1717          | 0.9220   |
 | 0.1391        | 2.0   | 3370 | 0.1757          | 0.9240   |
 | 0.0899        | 3.0   | 5055 | 0.2088          | 0.9106   |
-| 0.0538        | 4.0   | 6740 | 0.2464          | 0.8953   |
-| 0.0344        | 5.0   | 8425 | 0.2606          | 0.8950   |
 
 
 ### Framework versions
@@ -60,4 +57,4 @@ The following hyperparameters were used during training:
 - Transformers 4.24.0
 - Pytorch 2.0.1
 - Datasets 2.12.0
-- Tokenizers 0.11.0
+- Tokenizers 0.11.0