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README.md
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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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model-index:
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- name: hBERTv1_new_pretrain_48_mnli
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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: mnli
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split: validation_matched
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args: mnli
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.3273560876209883
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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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# hBERTv1_new_pretrain_48_mnli
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_48) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1024
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- Accuracy: 0.3274
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 1.1024 | 1.0 | 3068 | 1.0987 | 0.3545 |
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| 1.0989 | 2.0 | 6136 | 1.1008 | 0.3545 |
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| 1.0991 | 3.0 | 9204 | 1.0994 | 0.3182 |
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| 1.099 | 4.0 | 12272 | 1.0994 | 0.3182 |
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| 1.0991 | 5.0 | 15340 | 1.0975 | 0.3182 |
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| 1.0995 | 6.0 | 18408 | 1.1004 | 0.3182 |
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| 1.0992 | 7.0 | 21476 | 1.0997 | 0.3274 |
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| 1.0992 | 8.0 | 24544 | 1.0962 | 0.3545 |
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| 1.099 | 9.0 | 27612 | 1.1018 | 0.3182 |
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| 1.0991 | 10.0 | 30680 | 1.0981 | 0.3182 |
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| 1.0992 | 11.0 | 33748 | 1.0980 | 0.3545 |
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| 1.0993 | 12.0 | 36816 | 1.0967 | 0.3274 |
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| 1.0992 | 13.0 | 39884 | 1.1024 | 0.3274 |
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### Framework versions
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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
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