---
library_name: transformers
language:
- en
license: apache-2.0
base_model: google/bert_uncased_L-4_H-128_A-2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert_uncased_L-4_H-128_A-2_rte
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE RTE
      type: glue
      args: rte
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6173285198555957
---

<!-- 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. -->

# bert_uncased_L-4_H-128_A-2_rte

This model is a fine-tuned version of [google/bert_uncased_L-4_H-128_A-2](https://huggingface.co/google/bert_uncased_L-4_H-128_A-2) on the GLUE RTE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6659
- Accuracy: 0.6173

## 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
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6967        | 1.0   | 10   | 0.6907          | 0.5523   |
| 0.689         | 2.0   | 20   | 0.6875          | 0.5740   |
| 0.6832        | 3.0   | 30   | 0.6854          | 0.5379   |
| 0.6776        | 4.0   | 40   | 0.6809          | 0.5632   |
| 0.6694        | 5.0   | 50   | 0.6780          | 0.5812   |
| 0.6599        | 6.0   | 60   | 0.6749          | 0.5740   |
| 0.6469        | 7.0   | 70   | 0.6726          | 0.5993   |
| 0.6392        | 8.0   | 80   | 0.6712          | 0.5776   |
| 0.6221        | 9.0   | 90   | 0.6682          | 0.5884   |
| 0.6034        | 10.0  | 100  | 0.6684          | 0.5957   |
| 0.5867        | 11.0  | 110  | 0.6717          | 0.5993   |
| 0.5686        | 12.0  | 120  | 0.6690          | 0.6065   |
| 0.5596        | 13.0  | 130  | 0.6659          | 0.6173   |
| 0.5377        | 14.0  | 140  | 0.6720          | 0.6101   |
| 0.5249        | 15.0  | 150  | 0.6820          | 0.6029   |
| 0.5019        | 16.0  | 160  | 0.6896          | 0.6065   |
| 0.492         | 17.0  | 170  | 0.6977          | 0.6029   |
| 0.4786        | 18.0  | 180  | 0.7027          | 0.6173   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3