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: distilbert-base-uncased-finetuned-go_emotions_20220608_1
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: go_emotions
+      type: go_emotions
+      args: simplified
+    metrics:
+    - name: F1
+      type: f1
+      value: 0.5575026333429091
+    - name: Accuracy
+      type: accuracy
+      value: 0.43641725027644673
+---
+
+<!-- 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-base-uncased-finetuned-go_emotions_20220608_1
+
+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: 0.0857
+- F1: 0.5575
+- Roc Auc: 0.7242
+- Accuracy: 0.4364
+
+## 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
+| 0.173         | 1.0   | 679  | 0.1074          | 0.4245 | 0.6455  | 0.2976   |
+| 0.0989        | 2.0   | 1358 | 0.0903          | 0.5199 | 0.6974  | 0.3972   |
+| 0.0865        | 3.0   | 2037 | 0.0868          | 0.5504 | 0.7180  | 0.4263   |
+| 0.0806        | 4.0   | 2716 | 0.0860          | 0.5472 | 0.7160  | 0.4233   |
+| 0.0771        | 5.0   | 3395 | 0.0857          | 0.5575 | 0.7242  | 0.4364   |
+
+
+### Framework versions
+
+- Transformers 4.19.2
+- Pytorch 1.11.0+cu113
+- Datasets 2.2.2
+- Tokenizers 0.12.1