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: tiny-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: 0.7032085561497327
+    - name: F1
+      type: f1
+      value: 0.704229444708009
+---
+
+<!-- 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. -->
+
+# tiny-vanilla-target-tweet
+
+This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the tweet_eval dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9887
+- Accuracy: 0.7032
+- F1: 0.7042
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 1.1604        | 4.9   | 500  | 0.9784          | 0.6604   | 0.6290 |
+| 0.7656        | 9.8   | 1000 | 0.8273          | 0.7139   | 0.6905 |
+| 0.534         | 14.71 | 1500 | 0.8138          | 0.7219   | 0.7143 |
+| 0.3832        | 19.61 | 2000 | 0.8591          | 0.7086   | 0.7050 |
+| 0.2722        | 24.51 | 2500 | 0.9250          | 0.7112   | 0.7118 |
+| 0.1858        | 29.41 | 3000 | 0.9887          | 0.7032   | 0.7042 |
+
+
+### Framework versions
+
+- Transformers 4.25.1
+- Pytorch 1.12.1
+- Datasets 2.7.1
+- Tokenizers 0.13.2