update model card README.md

README.md

@@ -1,3 +1,92 @@
 ---
-license: mit
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- go_emotions
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: distilbert-go-emotions
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: go_emotions
+      type: go_emotions
+      args: simplified
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.42867674161444896
+    - name: Precision
+      type: precision
+      value: 0.4503794622630937
+    - name: Recall
+      type: recall
+      value: 0.5002719498073401
+    - name: F1
+      type: f1
+      value: 0.47024637118703766
 ---
+
+<!-- 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. -->
+
+# distilbert-go-emotions
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the go_emotions dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0907
+- Accuracy: 0.4287
+- Precision: 0.4504
+- Recall: 0.5003
+- F1: 0.4702
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 128
+- eval_batch_size: 128
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 6
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 1.0   | 340  | 0.1102          | 0.4125   | 0.2946    | 0.2139 | 0.2014 |
+| 0.1347        | 2.0   | 680  | 0.0890          | 0.3900   | 0.4252    | 0.4627 | 0.4262 |
+| 0.1347        | 3.0   | 1020 | 0.0860          | 0.4097   | 0.4344    | 0.4992 | 0.4578 |
+| 0.0771        | 4.0   | 1360 | 0.0864          | 0.4298   | 0.4561    | 0.4974 | 0.4701 |
+| 0.0771        | 5.0   | 1700 | 0.0891          | 0.4266   | 0.4522    | 0.4992 | 0.4703 |
+| 0.0617        | 6.0   | 2040 | 0.0907          | 0.4287   | 0.4504    | 0.5003 | 0.4702 |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.12.0
+- Datasets 2.1.0
+- Tokenizers 0.12.1