update model card README.md

README.md

@@ -4,9 +4,26 @@ tags:
 - generated_from_trainer
 datasets:
 - emotion
+metrics:
+- accuracy
+- f1
 model-index:
 - name: distilbert-base-uncased-finetuned-emotion
-  results: []
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: emotion
+      type: emotion
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.918
+    - name: F1
+      type: f1
+      value: 0.9182094401352938
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,14 +33,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 0.2242
-- eval_accuracy: 0.927
-- eval_f1: 0.9271
-- eval_runtime: 89.316
-- eval_samples_per_second: 22.392
-- eval_steps_per_second: 0.358
-- epoch: 1.0
-- step: 250
+- Loss: 0.2287
+- Accuracy: 0.918
+- F1: 0.9182
 
 ## Model description
 
@@ -50,9 +62,17 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 2
 
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.8478        | 1.0   | 250  | 0.3294          | 0.9015   | 0.8980 |
+| 0.2616        | 2.0   | 500  | 0.2287          | 0.918    | 0.9182 |
+
+
 ### Framework versions
 
-- Transformers 4.16.2
-- Pytorch 1.10.2+cpu
-- Datasets 1.18.3
-- Tokenizers 0.11.0
+- Transformers 4.17.0
+- Pytorch 1.10.0+cu111
+- Datasets 1.18.4
+- Tokenizers 0.11.6