update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: ArBERT-finetuned-fnd
+  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. -->
+
+# ArBERT-finetuned-fnd
+
+This model is a fine-tuned version of [UBC-NLP/ARBERT](https://huggingface.co/UBC-NLP/ARBERT) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4956
+- Macro F1: 0.7629
+- Accuracy: 0.7752
+- Precision: 0.7737
+- Recall: 0.7584
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 25
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 7
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|
+| 0.5033        | 1.0   | 1597 | 0.4831          | 0.7507   | 0.7543   | 0.7495    | 0.7554 |
+| 0.3858        | 2.0   | 3194 | 0.4956          | 0.7629   | 0.7752   | 0.7737    | 0.7584 |
+| 0.2675        | 3.0   | 4791 | 0.5964          | 0.7593   | 0.7712   | 0.7685    | 0.7552 |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.11.0
+- Datasets 2.1.0
+- Tokenizers 0.12.1