---
library_name: transformers
language:
- en
license: apache-2.0
base_model: google/bert_uncased_L-2_H-128_A-2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert_uncased_L-2_H-128_A-2_mnli
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MNLI
      type: glue
      args: mnli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7112489829129374
---

<!-- 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-2_H-128_A-2_mnli

This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the GLUE MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6901
- Accuracy: 0.7112

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9155        | 1.0   | 1534  | 0.8197          | 0.6342   |
| 0.8189        | 2.0   | 3068  | 0.7689          | 0.6626   |
| 0.7747        | 3.0   | 4602  | 0.7417          | 0.6760   |
| 0.7449        | 4.0   | 6136  | 0.7285          | 0.6852   |
| 0.7198        | 5.0   | 7670  | 0.7111          | 0.6934   |
| 0.6996        | 6.0   | 9204  | 0.7118          | 0.6977   |
| 0.6812        | 7.0   | 10738 | 0.7005          | 0.7030   |
| 0.6649        | 8.0   | 12272 | 0.6981          | 0.7043   |
| 0.6491        | 9.0   | 13806 | 0.7057          | 0.7036   |
| 0.6358        | 10.0  | 15340 | 0.6983          | 0.7077   |
| 0.6224        | 11.0  | 16874 | 0.6966          | 0.7064   |
| 0.6109        | 12.0  | 18408 | 0.7001          | 0.7145   |
| 0.5994        | 13.0  | 19942 | 0.7014          | 0.7113   |
| 0.5872        | 14.0  | 21476 | 0.7061          | 0.7084   |
| 0.5779        | 15.0  | 23010 | 0.7054          | 0.7168   |
| 0.5681        | 16.0  | 24544 | 0.7059          | 0.7147   |


### Framework versions

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