update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- emotion
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bertweet-base-finetuned-emotion
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: emotion
+      type: emotion
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.929
+    - name: F1
+      type: f1
+      value: 0.9295613935787139
+---
+
+<!-- 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. -->
+
+# bertweet-base-finetuned-emotion
+
+This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on the emotion dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1737
+- Accuracy: 0.929
+- F1: 0.9296
+
+## 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: 2e-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: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.9469        | 1.0   | 250  | 0.3643          | 0.895    | 0.8921 |
+| 0.2807        | 2.0   | 500  | 0.2173          | 0.9245   | 0.9252 |
+| 0.1749        | 3.0   | 750  | 0.1859          | 0.926    | 0.9266 |
+| 0.1355        | 4.0   | 1000 | 0.1737          | 0.929    | 0.9296 |
+
+
+### Framework versions
+
+- Transformers 4.13.0
+- Pytorch 1.11.0+cu113
+- Datasets 1.16.1
+- Tokenizers 0.10.3