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---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: hBERTv1_new_pretrain_w_init__mnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MNLI
type: glue
config: mnli
split: validation_matched
args: mnli
metrics:
- name: Accuracy
type: accuracy
value: 0.318246541903987
---
<!-- 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__mnli
This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init) on the GLUE MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0963
- Accuracy: 0.3182
## 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: 0.0005
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1346 | 1.0 | 3068 | 1.0988 | 0.3545 |
| 1.1013 | 2.0 | 6136 | 1.0963 | 0.3182 |
| 1.1611 | 3.0 | 9204 | 1.0990 | 0.3274 |
| 1.0988 | 4.0 | 12272 | 1.0988 | 0.3545 |
| 1.0987 | 5.0 | 15340 | 1.0988 | 0.3545 |
| 1.0985 | 6.0 | 18408 | 1.0990 | 0.3274 |
| 1.0987 | 7.0 | 21476 | 1.0990 | 0.3274 |
### Framework versions
- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
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