---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: best_model-sst-2-16-13
  results: []
---

<!-- 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. -->

# best_model-sst-2-16-13

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5420
- Accuracy: 0.8125

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 150

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1    | 0.6945          | 0.5938   |
| No log        | 2.0   | 2    | 0.6945          | 0.5938   |
| No log        | 3.0   | 3    | 0.6945          | 0.5938   |
| No log        | 4.0   | 4    | 0.6944          | 0.5938   |
| No log        | 5.0   | 5    | 0.6944          | 0.5938   |
| No log        | 6.0   | 6    | 0.6944          | 0.5938   |
| No log        | 7.0   | 7    | 0.6944          | 0.5938   |
| No log        | 8.0   | 8    | 0.6943          | 0.5938   |
| No log        | 9.0   | 9    | 0.6943          | 0.5938   |
| 0.7032        | 10.0  | 10   | 0.6943          | 0.5938   |
| 0.7032        | 11.0  | 11   | 0.6942          | 0.5938   |
| 0.7032        | 12.0  | 12   | 0.6942          | 0.5938   |
| 0.7032        | 13.0  | 13   | 0.6941          | 0.5938   |
| 0.7032        | 14.0  | 14   | 0.6940          | 0.5938   |
| 0.7032        | 15.0  | 15   | 0.6940          | 0.5938   |
| 0.7032        | 16.0  | 16   | 0.6939          | 0.5938   |
| 0.7032        | 17.0  | 17   | 0.6938          | 0.5938   |
| 0.7032        | 18.0  | 18   | 0.6937          | 0.5938   |
| 0.7032        | 19.0  | 19   | 0.6936          | 0.5938   |
| 0.709         | 20.0  | 20   | 0.6935          | 0.5938   |
| 0.709         | 21.0  | 21   | 0.6934          | 0.5938   |
| 0.709         | 22.0  | 22   | 0.6933          | 0.5938   |
| 0.709         | 23.0  | 23   | 0.6932          | 0.5938   |
| 0.709         | 24.0  | 24   | 0.6931          | 0.5938   |
| 0.709         | 25.0  | 25   | 0.6930          | 0.5938   |
| 0.709         | 26.0  | 26   | 0.6928          | 0.5938   |
| 0.709         | 27.0  | 27   | 0.6927          | 0.5938   |
| 0.709         | 28.0  | 28   | 0.6926          | 0.5938   |
| 0.709         | 29.0  | 29   | 0.6924          | 0.5938   |
| 0.6984        | 30.0  | 30   | 0.6923          | 0.5938   |
| 0.6984        | 31.0  | 31   | 0.6921          | 0.5938   |
| 0.6984        | 32.0  | 32   | 0.6920          | 0.5938   |
| 0.6984        | 33.0  | 33   | 0.6918          | 0.5938   |
| 0.6984        | 34.0  | 34   | 0.6916          | 0.5938   |
| 0.6984        | 35.0  | 35   | 0.6915          | 0.5938   |
| 0.6984        | 36.0  | 36   | 0.6913          | 0.5938   |
| 0.6984        | 37.0  | 37   | 0.6911          | 0.5938   |
| 0.6984        | 38.0  | 38   | 0.6909          | 0.5938   |
| 0.6984        | 39.0  | 39   | 0.6907          | 0.5938   |
| 0.6833        | 40.0  | 40   | 0.6905          | 0.5938   |
| 0.6833        | 41.0  | 41   | 0.6903          | 0.5938   |
| 0.6833        | 42.0  | 42   | 0.6901          | 0.5938   |
| 0.6833        | 43.0  | 43   | 0.6899          | 0.5938   |
| 0.6833        | 44.0  | 44   | 0.6897          | 0.5938   |
| 0.6833        | 45.0  | 45   | 0.6895          | 0.5938   |
| 0.6833        | 46.0  | 46   | 0.6893          | 0.5938   |
| 0.6833        | 47.0  | 47   | 0.6890          | 0.5938   |
| 0.6833        | 48.0  | 48   | 0.6888          | 0.5938   |
| 0.6833        | 49.0  | 49   | 0.6885          | 0.5938   |
| 0.6831        | 50.0  | 50   | 0.6882          | 0.5938   |
| 0.6831        | 51.0  | 51   | 0.6879          | 0.5938   |
| 0.6831        | 52.0  | 52   | 0.6876          | 0.5938   |
| 0.6831        | 53.0  | 53   | 0.6873          | 0.5938   |
| 0.6831        | 54.0  | 54   | 0.6870          | 0.5938   |
| 0.6831        | 55.0  | 55   | 0.6867          | 0.625    |
| 0.6831        | 56.0  | 56   | 0.6863          | 0.625    |
| 0.6831        | 57.0  | 57   | 0.6860          | 0.625    |
| 0.6831        | 58.0  | 58   | 0.6856          | 0.625    |
| 0.6831        | 59.0  | 59   | 0.6852          | 0.625    |
| 0.669         | 60.0  | 60   | 0.6848          | 0.625    |
| 0.669         | 61.0  | 61   | 0.6844          | 0.625    |
| 0.669         | 62.0  | 62   | 0.6839          | 0.625    |
| 0.669         | 63.0  | 63   | 0.6835          | 0.625    |
| 0.669         | 64.0  | 64   | 0.6830          | 0.625    |
| 0.669         | 65.0  | 65   | 0.6824          | 0.625    |
| 0.669         | 66.0  | 66   | 0.6819          | 0.625    |
| 0.669         | 67.0  | 67   | 0.6814          | 0.625    |
| 0.669         | 68.0  | 68   | 0.6808          | 0.625    |
| 0.669         | 69.0  | 69   | 0.6802          | 0.625    |
| 0.6556        | 70.0  | 70   | 0.6796          | 0.625    |
| 0.6556        | 71.0  | 71   | 0.6789          | 0.625    |
| 0.6556        | 72.0  | 72   | 0.6782          | 0.625    |
| 0.6556        | 73.0  | 73   | 0.6774          | 0.625    |
| 0.6556        | 74.0  | 74   | 0.6766          | 0.6562   |
| 0.6556        | 75.0  | 75   | 0.6757          | 0.6562   |
| 0.6556        | 76.0  | 76   | 0.6747          | 0.6562   |
| 0.6556        | 77.0  | 77   | 0.6736          | 0.6562   |
| 0.6556        | 78.0  | 78   | 0.6725          | 0.6562   |
| 0.6556        | 79.0  | 79   | 0.6713          | 0.6562   |
| 0.6248        | 80.0  | 80   | 0.6700          | 0.6562   |
| 0.6248        | 81.0  | 81   | 0.6687          | 0.6562   |
| 0.6248        | 82.0  | 82   | 0.6673          | 0.6562   |
| 0.6248        | 83.0  | 83   | 0.6660          | 0.6562   |
| 0.6248        | 84.0  | 84   | 0.6647          | 0.6562   |
| 0.6248        | 85.0  | 85   | 0.6635          | 0.6562   |
| 0.6248        | 86.0  | 86   | 0.6622          | 0.6562   |
| 0.6248        | 87.0  | 87   | 0.6603          | 0.5938   |
| 0.6248        | 88.0  | 88   | 0.6586          | 0.5938   |
| 0.6248        | 89.0  | 89   | 0.6574          | 0.5938   |
| 0.6013        | 90.0  | 90   | 0.6565          | 0.5938   |
| 0.6013        | 91.0  | 91   | 0.6557          | 0.5938   |
| 0.6013        | 92.0  | 92   | 0.6548          | 0.5938   |
| 0.6013        | 93.0  | 93   | 0.6541          | 0.625    |
| 0.6013        | 94.0  | 94   | 0.6538          | 0.625    |
| 0.6013        | 95.0  | 95   | 0.6537          | 0.625    |
| 0.6013        | 96.0  | 96   | 0.6531          | 0.625    |
| 0.6013        | 97.0  | 97   | 0.6522          | 0.625    |
| 0.6013        | 98.0  | 98   | 0.6518          | 0.625    |
| 0.6013        | 99.0  | 99   | 0.6515          | 0.6562   |
| 0.5622        | 100.0 | 100  | 0.6502          | 0.6562   |
| 0.5622        | 101.0 | 101  | 0.6481          | 0.6562   |
| 0.5622        | 102.0 | 102  | 0.6457          | 0.6562   |
| 0.5622        | 103.0 | 103  | 0.6434          | 0.6562   |
| 0.5622        | 104.0 | 104  | 0.6411          | 0.6562   |
| 0.5622        | 105.0 | 105  | 0.6384          | 0.7188   |
| 0.5622        | 106.0 | 106  | 0.6362          | 0.6875   |
| 0.5622        | 107.0 | 107  | 0.6338          | 0.6875   |
| 0.5622        | 108.0 | 108  | 0.6311          | 0.6875   |
| 0.5622        | 109.0 | 109  | 0.6281          | 0.6562   |
| 0.5022        | 110.0 | 110  | 0.6236          | 0.6875   |
| 0.5022        | 111.0 | 111  | 0.6193          | 0.6875   |
| 0.5022        | 112.0 | 112  | 0.6141          | 0.6562   |
| 0.5022        | 113.0 | 113  | 0.6088          | 0.6875   |
| 0.5022        | 114.0 | 114  | 0.6046          | 0.6875   |
| 0.5022        | 115.0 | 115  | 0.6024          | 0.6875   |
| 0.5022        | 116.0 | 116  | 0.6014          | 0.6875   |
| 0.5022        | 117.0 | 117  | 0.6004          | 0.6875   |
| 0.5022        | 118.0 | 118  | 0.5993          | 0.6875   |
| 0.5022        | 119.0 | 119  | 0.5982          | 0.6875   |
| 0.4576        | 120.0 | 120  | 0.5969          | 0.6875   |
| 0.4576        | 121.0 | 121  | 0.5957          | 0.6875   |
| 0.4576        | 122.0 | 122  | 0.5944          | 0.7188   |
| 0.4576        | 123.0 | 123  | 0.5929          | 0.7188   |
| 0.4576        | 124.0 | 124  | 0.5916          | 0.7188   |
| 0.4576        | 125.0 | 125  | 0.5903          | 0.7188   |
| 0.4576        | 126.0 | 126  | 0.5887          | 0.7188   |
| 0.4576        | 127.0 | 127  | 0.5873          | 0.7188   |
| 0.4576        | 128.0 | 128  | 0.5857          | 0.75     |
| 0.4576        | 129.0 | 129  | 0.5837          | 0.75     |
| 0.4105        | 130.0 | 130  | 0.5819          | 0.75     |
| 0.4105        | 131.0 | 131  | 0.5797          | 0.75     |
| 0.4105        | 132.0 | 132  | 0.5781          | 0.75     |
| 0.4105        | 133.0 | 133  | 0.5770          | 0.75     |
| 0.4105        | 134.0 | 134  | 0.5756          | 0.75     |
| 0.4105        | 135.0 | 135  | 0.5734          | 0.75     |
| 0.4105        | 136.0 | 136  | 0.5714          | 0.75     |
| 0.4105        | 137.0 | 137  | 0.5694          | 0.75     |
| 0.4105        | 138.0 | 138  | 0.5673          | 0.75     |
| 0.4105        | 139.0 | 139  | 0.5651          | 0.75     |
| 0.3744        | 140.0 | 140  | 0.5628          | 0.75     |
| 0.3744        | 141.0 | 141  | 0.5605          | 0.7812   |
| 0.3744        | 142.0 | 142  | 0.5581          | 0.7812   |
| 0.3744        | 143.0 | 143  | 0.5555          | 0.7812   |
| 0.3744        | 144.0 | 144  | 0.5532          | 0.7812   |
| 0.3744        | 145.0 | 145  | 0.5510          | 0.7812   |
| 0.3744        | 146.0 | 146  | 0.5489          | 0.7812   |
| 0.3744        | 147.0 | 147  | 0.5470          | 0.7812   |
| 0.3744        | 148.0 | 148  | 0.5453          | 0.7812   |
| 0.3744        | 149.0 | 149  | 0.5435          | 0.7812   |
| 0.3294        | 150.0 | 150  | 0.5420          | 0.8125   |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.4.0
- Tokenizers 0.13.3