update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- accuracy
+- f1
+model-index:
+- name: hBERTv1_new_pretrain_w_init_48_qqp
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: glue
+      type: glue
+      config: qqp
+      split: validation
+      args: qqp
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.855107593371259
+    - name: F1
+      type: f1
+      value: 0.8099409512685743
+---
+
+<!-- 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. -->
+
+# hBERTv1_new_pretrain_w_init_48_qqp
+
+This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48) on the glue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3726
+- Accuracy: 0.8551
+- F1: 0.8099
+- Combined Score: 0.8325
+
+## 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: 4e-05
+- train_batch_size: 128
+- eval_batch_size: 128
+- seed: 10
+- distributed_type: multi-GPU
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 50
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Combined Score |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.4637        | 1.0   | 2843  | 0.3907          | 0.8136   | 0.7636 | 0.7886         |
+| 0.363         | 2.0   | 5686  | 0.3536          | 0.8338   | 0.7900 | 0.8119         |
+| 0.3211        | 3.0   | 8529  | 0.3476          | 0.8430   | 0.7845 | 0.8138         |
+| 0.2906        | 4.0   | 11372 | 0.3539          | 0.8531   | 0.8059 | 0.8295         |
+| 0.2603        | 5.0   | 14215 | 0.3531          | 0.8531   | 0.8017 | 0.8274         |
+| 0.2373        | 6.0   | 17058 | 0.3716          | 0.8561   | 0.8089 | 0.8325         |
+| 0.2175        | 7.0   | 19901 | 0.3553          | 0.8565   | 0.8123 | 0.8344         |
+| 0.1957        | 8.0   | 22744 | 0.3726          | 0.8551   | 0.8099 | 0.8325         |
+
+
+### Framework versions
+
+- Transformers 4.29.2
+- Pytorch 1.14.0a0+410ce96
+- Datasets 2.12.0
+- Tokenizers 0.13.3