update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- eoir_privacy
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert_uncased_L-4_H-512_A-8-finetuned-eoir_privacy
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: eoir_privacy
+      type: eoir_privacy
+      config: all
+      split: train
+      args: all
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9175035868005739
+    - name: F1
+      type: f1
+      value: 0.8092868988391376
+---
+
+<!-- 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. -->
+
+# bert_uncased_L-4_H-512_A-8-finetuned-eoir_privacy
+
+This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the eoir_privacy dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2159
+- Accuracy: 0.9175
+- F1: 0.8093
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 128
+- 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     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| No log        | 1.0   | 63   | 0.2343          | 0.9125   | 0.7953 |
+| No log        | 2.0   | 126  | 0.2269          | 0.9110   | 0.8006 |
+| No log        | 3.0   | 189  | 0.2159          | 0.9175   | 0.8093 |
+
+
+### Framework versions
+
+- Transformers 4.21.1
+- Pytorch 1.12.1+cu113
+- Datasets 2.4.0
+- Tokenizers 0.12.1