update model card README.md

README.md

@@ -1,3 +1,89 @@
 ---
 license: mit
+tags:
+- generated_from_trainer
+datasets:
+- go_emotions
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: roberta-large-go-emotions-3
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: go_emotions
+      type: go_emotions
+      args: simplified
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.44452635458901585
+    - name: Precision
+      type: precision
+      value: 0.5241481690233145
+    - name: Recall
+      type: recall
+      value: 0.532779745019394
+    - name: F1
+      type: f1
+      value: 0.5160548869396229
 ---
+
+<!-- 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. -->
+
+# roberta-large-go-emotions-3
+
+This model is a fine-tuned version of [tasinhoque/roberta-large-go-emotions](https://huggingface.co/tasinhoque/roberta-large-go-emotions) on the go_emotions dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0956
+- Accuracy: 0.4445
+- Precision: 0.5241
+- Recall: 0.5328
+- F1: 0.5161
+
+## 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 1.0   | 340  | 0.0862          | 0.4292   | 0.5012    | 0.5558 | 0.5208 |
+| 0.0597        | 2.0   | 680  | 0.0924          | 0.4329   | 0.5164    | 0.5362 | 0.5151 |
+| 0.0597        | 3.0   | 1020 | 0.0956          | 0.4445   | 0.5241    | 0.5328 | 0.5161 |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.12.0
+- Datasets 2.1.0
+- Tokenizers 0.12.1