Model save

README.md

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+---
+base_model: gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48
+tags:
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- accuracy
+model-index:
+- name: hBERTv2_new_pretrain_w_init_48_ver2_qnli
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: glue
+      type: glue
+      config: qnli
+      split: validation
+      args: qnli
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.4946000366099213
+---
+
+<!-- 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. -->
+
+# hBERTv2_new_pretrain_w_init_48_ver2_qnli
+
+This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48) on the glue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6931
+- Accuracy: 0.4946
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 10
+- distributed_type: multi-GPU
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.7008        | 1.0   | 1637  | 0.6943          | 0.5054   |
+| 0.6946        | 2.0   | 3274  | 0.6931          | 0.5054   |
+| 0.6938        | 3.0   | 4911  | 0.6932          | 0.4946   |
+| 0.6943        | 4.0   | 6548  | 0.6934          | 0.5054   |
+| 0.694         | 5.0   | 8185  | 0.6933          | 0.4946   |
+| 0.6932        | 6.0   | 9822  | 0.6931          | 0.5054   |
+| 0.6934        | 7.0   | 11459 | 0.6931          | 0.5054   |
+| 0.6932        | 8.0   | 13096 | 0.6931          | 0.5054   |
+| 0.6932        | 9.0   | 14733 | 0.6932          | 0.4946   |
+| 0.6932        | 10.0  | 16370 | 0.6933          | 0.4946   |
+| 0.6932        | 11.0  | 18007 | 0.6931          | 0.5054   |
+| 0.6932        | 12.0  | 19644 | 0.6931          | 0.5054   |
+| 0.6932        | 13.0  | 21281 | 0.6931          | 0.4946   |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 1.14.0a0+410ce96
+- Datasets 2.14.5
+- Tokenizers 0.14.1

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