transformers pytorch tensorboard hybridbert text-classification generated_from_trainer en dataset:glue model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
language:
- en
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: hBERTv1_new_pretrain_48_emb_com_rte
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE RTE
      type: glue
      config: rte
      split: validation
      args: rte
    metrics:
    - type: accuracy
      value: 0.4729241877256318
      name: Accuracy
---

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# hBERTv1_new_pretrain_48_emb_com_rte

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_emb_compress_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_emb_compress_48) on the GLUE RTE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6935
- Accuracy: 0.4729

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7535        | 1.0   | 20   | 0.6953          | 0.4729   |
| 0.7205        | 2.0   | 40   | 0.6935          | 0.4729   |
| 0.7032        | 3.0   | 60   | 0.6941          | 0.5271   |
| 0.6969        | 4.0   | 80   | 0.7111          | 0.4729   |
| 0.7173        | 5.0   | 100  | 0.7630          | 0.5090   |
| 0.6969        | 6.0   | 120  | 0.7185          | 0.4946   |
| 0.6389        | 7.0   | 140  | 0.8181          | 0.5307   |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
