update model card README.md

README.md

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+---
+license: mit
+base_model: digitalepidemiologylab/covid-twitter-bert-v2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: covid-twitter-bert-v2_epoch3_batch4_lr2e-05_w0.01
+  results: []
+---
+
+<!-- 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. -->
+
+# covid-twitter-bert-v2_epoch3_batch4_lr2e-05_w0.01
+
+This model is a fine-tuned version of [digitalepidemiologylab/covid-twitter-bert-v2](https://huggingface.co/digitalepidemiologylab/covid-twitter-bert-v2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5108
+- Accuracy: 0.7497
+- F1: 0.6879
+- Precision: 0.6425
+- Recall: 0.7403
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.6731        | 1.0   | 788  | 0.6654          | 0.6274   | 0.0    | 0.0       | 0.0    |
+| 0.6727        | 2.0   | 1576 | 0.6396          | 0.6274   | 0.0    | 0.0       | 0.0    |
+| 0.6462        | 3.0   | 2364 | 0.5108          | 0.7497   | 0.6879 | 0.6425    | 0.7403 |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.3
+- Tokenizers 0.13.3