update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- go_emotions
+metrics:
+- f1
+- accuracy
+model-index:
+- name: bert-base-goemotions
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: go_emotions
+      type: go_emotions
+      config: simplified
+      split: validation
+      args: simplified
+    metrics:
+    - name: F1
+      type: f1
+      value: 0.5726694586629439
+    - name: Accuracy
+      type: accuracy
+      value: 0.4375230372281607
+---
+
+<!-- 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. -->
+
+# bert-base-goemotions
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the go_emotions dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1539
+- F1: 0.5727
+- Roc Auc: 0.7796
+- Accuracy: 0.4375
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | F1     | Roc Auc | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
+| 0.0833        | 1.0   | 2714  | 0.0876          | 0.5453 | 0.7189  | 0.4243   |
+| 0.0719        | 2.0   | 5428  | 0.0867          | 0.5586 | 0.7322  | 0.4399   |
+| 0.0575        | 3.0   | 8142  | 0.0943          | 0.5736 | 0.7523  | 0.4665   |
+| 0.0411        | 4.0   | 10856 | 0.1064          | 0.5655 | 0.7580  | 0.4574   |
+| 0.0301        | 5.0   | 13570 | 0.1167          | 0.5622 | 0.7591  | 0.4517   |
+| 0.0217        | 6.0   | 16284 | 0.1279          | 0.5579 | 0.7648  | 0.4375   |
+| 0.015         | 7.0   | 18998 | 0.1367          | 0.5663 | 0.7759  | 0.4333   |
+| 0.0102        | 8.0   | 21712 | 0.1445          | 0.5695 | 0.7793  | 0.4322   |
+| 0.0077        | 9.0   | 24426 | 0.1491          | 0.5725 | 0.7795  | 0.4366   |
+| 0.0057        | 10.0  | 27140 | 0.1539          | 0.5727 | 0.7796  | 0.4375   |
+
+
+### Framework versions
+
+- Transformers 4.26.0
+- Pytorch 1.13.1+cu116
+- Datasets 2.9.0
+- Tokenizers 0.13.2