---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: hBERTv2_rte
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE RTE
      type: glue
      config: rte
      split: validation
      args: rte
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5487364620938628
---

<!-- 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_rte

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2](https://huggingface.co/gokuls/bert_12_layer_model_v2) on the GLUE RTE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6896
- Accuracy: 0.5487

## 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: 5e-05
- train_batch_size: 256
- eval_batch_size: 256
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7231        | 1.0   | 10   | 0.7175          | 0.4549   |
| 0.702         | 2.0   | 20   | 0.7053          | 0.4729   |
| 0.6982        | 3.0   | 30   | 0.6976          | 0.4585   |
| 0.7008        | 4.0   | 40   | 0.7261          | 0.4657   |
| 0.7022        | 5.0   | 50   | 0.7142          | 0.4946   |
| 0.6867        | 6.0   | 60   | 0.6943          | 0.4801   |
| 0.6796        | 7.0   | 70   | 0.6896          | 0.5487   |
| 0.6614        | 8.0   | 80   | 0.7151          | 0.5162   |
| 0.6303        | 9.0   | 90   | 0.7244          | 0.5271   |
| 0.602         | 10.0  | 100  | 0.7570          | 0.4729   |
| 0.5761        | 11.0  | 110  | 0.7605          | 0.5379   |
| 0.5664        | 12.0  | 120  | 0.8160          | 0.5235   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.10.1
- Tokenizers 0.13.2