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hBERTv1_new_pretrain_w_init_48_mrpc

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+ ---
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - glue
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+ metrics:
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+ - accuracy
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+ - f1
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+ model-index:
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+ - name: hBERTv1_new_pretrain_w_init_48_mrpc
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: glue
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+ type: glue
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+ config: mrpc
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+ split: validation
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+ args: mrpc
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.678921568627451
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+ - name: F1
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+ type: f1
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+ value: 0.7827529021558872
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # hBERTv1_new_pretrain_w_init_48_mrpc
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+
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+ 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.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7737
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+ - Accuracy: 0.6789
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+ - F1: 0.7828
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+ - Combined Score: 0.7308
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 4e-05
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+ - train_batch_size: 128
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+ - eval_batch_size: 128
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+ - seed: 10
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+ - distributed_type: multi-GPU
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 50
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
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+ | 0.6607 | 1.0 | 29 | 0.6262 | 0.6838 | 0.8122 | 0.7480 |
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+ | 0.6421 | 2.0 | 58 | 0.6368 | 0.6838 | 0.8122 | 0.7480 |
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+ | 0.6411 | 3.0 | 87 | 0.6258 | 0.6838 | 0.8122 | 0.7480 |
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+ | 0.6406 | 4.0 | 116 | 0.6422 | 0.6838 | 0.8122 | 0.7480 |
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+ | 0.6364 | 5.0 | 145 | 0.6263 | 0.6838 | 0.8122 | 0.7480 |
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+ | 0.6322 | 6.0 | 174 | 0.6253 | 0.6838 | 0.8122 | 0.7480 |
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+ | 0.6398 | 7.0 | 203 | 0.6289 | 0.6838 | 0.8122 | 0.7480 |
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+ | 0.6363 | 8.0 | 232 | 0.6267 | 0.6838 | 0.8122 | 0.7480 |
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+ | 0.6374 | 9.0 | 261 | 0.6375 | 0.6838 | 0.8122 | 0.7480 |
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+ | 0.6374 | 10.0 | 290 | 0.6248 | 0.6838 | 0.8122 | 0.7480 |
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+ | 0.638 | 11.0 | 319 | 0.6262 | 0.6838 | 0.8122 | 0.7480 |
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+ | 0.6353 | 12.0 | 348 | 0.6236 | 0.6838 | 0.8122 | 0.7480 |
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+ | 0.6338 | 13.0 | 377 | 0.6263 | 0.6838 | 0.8122 | 0.7480 |
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+ | 0.637 | 14.0 | 406 | 0.6250 | 0.6838 | 0.8122 | 0.7480 |
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+ | 0.6375 | 15.0 | 435 | 0.6229 | 0.6838 | 0.8122 | 0.7480 |
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+ | 0.7037 | 16.0 | 464 | 0.6438 | 0.6838 | 0.8122 | 0.7480 |
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+ | 0.6198 | 17.0 | 493 | 0.6242 | 0.6961 | 0.8038 | 0.7499 |
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+ | 0.5847 | 18.0 | 522 | 0.6260 | 0.6740 | 0.7742 | 0.7241 |
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+ | 0.4983 | 19.0 | 551 | 0.7174 | 0.7034 | 0.8158 | 0.7596 |
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+ | 0.4245 | 20.0 | 580 | 0.7737 | 0.6789 | 0.7828 | 0.7308 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.29.2
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+ - Pytorch 1.14.0a0+410ce96
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.3