update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- tweet_eval
+metrics:
+- accuracy
+- f1
+model-index:
+- name: medium-vanilla-target-tweet
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: tweet_eval
+      type: tweet_eval
+      config: emotion
+      split: train
+      args: emotion
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.7754010695187166
+    - name: F1
+      type: f1
+      value: 0.7745943137047872
+---
+
+<!-- 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. -->
+
+# medium-vanilla-target-tweet
+
+This model is a fine-tuned version of [google/bert_uncased_L-8_H-512_A-8](https://huggingface.co/google/bert_uncased_L-8_H-512_A-8) on the tweet_eval dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.9845
+- Accuracy: 0.7754
+- F1: 0.7746
+
+## 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: 3e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: constant
+- num_epochs: 200
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.4989        | 4.9   | 500  | 0.8358          | 0.7620   | 0.7589 |
+| 0.0702        | 9.8   | 1000 | 1.3142          | 0.7674   | 0.7683 |
+| 0.0233        | 14.71 | 1500 | 1.4760          | 0.7647   | 0.7650 |
+| 0.015         | 19.61 | 2000 | 1.5151          | 0.7834   | 0.7841 |
+| 0.0062        | 24.51 | 2500 | 1.6094          | 0.7968   | 0.7947 |
+| 0.0113        | 29.41 | 3000 | 1.9273          | 0.7540   | 0.7537 |
+| 0.0157        | 34.31 | 3500 | 2.0073          | 0.7433   | 0.7460 |
+| 0.0124        | 39.22 | 4000 | 1.9845          | 0.7754   | 0.7746 |
+
+
+### Framework versions
+
+- Transformers 4.25.1
+- Pytorch 1.12.1
+- Datasets 2.7.1
+- Tokenizers 0.13.2