Update README.md

README.md

@@ -4,11 +4,52 @@ datasets:
 language:
 - en
 library_name: transformers
+model-index:
+- name: text-classification-goemotions
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: go_emotions
+      type: multilabel_classification
+      config: simplified
+      split: test
+      args: simplified
+    metrics:
+    - name: F1
+      type: f1
+      value: 0.487
 ---
-# Metrics
 
-| Metric             | Set         | Score    |
-|--------------------|-------------|----------|
-| F1 macro score     | Validation  | 0.484898 |
-| F1 macro score     | Test        | 0.486890 |
+# Text Classification GoEmotions
+
+This model is a fined-tuned version of [nreimers/MiniLMv2-L6-H384-distilled-from-RoBERTa-Large](https://huggingface.co/nreimers/MiniLMv2-L6-H384-distilled-from-RoBERTa-Large) on the on the [go_emotions](https://huggingface.co/datasets/go_emotions) dataset using [tasinho/text-classification-goemotions](https://huggingface.co/tasinhoque/text-classification-goemotions) as teacher model.
+
+# Load the Model
+
+```py
+from transformers import pipeline
+
+pipe = pipeline(model='Ngit/MiniLMv2-L6-H384-goemotions-v2', task='text-classification')
+pipe("I am angry")
+# [{'label': 'anger', 'score': 0.9722517132759094}]
+```
+
+The following hyperparameters were used during training:
+- learning_rate: 6e-05
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 40
+
+
+# Metrics (comparison with teacher model)
+
+| Teacher (params)    |   Student (params)     | Set         | Score (teacher)    |    Score (student)      |
+|--------------------|-------------|----------|--------| --------|
+| tasinhoque/text-classification-goemotions (355M) |      MiniLMv2-L6-H384-goemotions-v2    | Validation  | 0.514252 |0.484898 |
+| tasinhoque/text-classification-goemotions (33M) |      MiniLMv2-L6-H384-goemotions-v2    | Test  | 0.501937 |  0.486890 |