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---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: hBERTv2_new_pretrain_48_mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
config: mrpc
split: validation
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 0.6936274509803921
- name: F1
type: f1
value: 0.8091603053435115
---
<!-- 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_48_mrpc
This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_48) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5996
- Accuracy: 0.6936
- F1: 0.8092
- Combined Score: 0.7514
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6634 | 1.0 | 29 | 0.6017 | 0.6863 | 0.7881 | 0.7372 |
| 0.6054 | 2.0 | 58 | 0.6601 | 0.6691 | 0.7316 | 0.7004 |
| 0.5623 | 3.0 | 87 | 0.5996 | 0.6936 | 0.8092 | 0.7514 |
| 0.4773 | 4.0 | 116 | 0.6380 | 0.7010 | 0.8057 | 0.7534 |
| 0.3781 | 5.0 | 145 | 0.8476 | 0.6471 | 0.7391 | 0.6931 |
| 0.258 | 6.0 | 174 | 0.8257 | 0.6642 | 0.7514 | 0.7078 |
| 0.2236 | 7.0 | 203 | 1.1873 | 0.6495 | 0.7451 | 0.6973 |
| 0.1818 | 8.0 | 232 | 1.2389 | 0.6029 | 0.6908 | 0.6469 |
### Framework versions
- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
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