---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-uncased-sst-2-16-42
  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. -->

# bert-base-uncased-sst-2-16-42

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: 0.4392
- Accuracy: 0.7812

## 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    | 0.5342          | 0.6875   |
| No log        | 2.0   | 2    | 0.5341          | 0.6875   |
| No log        | 3.0   | 3    | 0.5340          | 0.6875   |
| No log        | 4.0   | 4    | 0.5339          | 0.6875   |
| No log        | 5.0   | 5    | 0.5337          | 0.6875   |
| No log        | 6.0   | 6    | 0.5335          | 0.6875   |
| No log        | 7.0   | 7    | 0.5332          | 0.6875   |
| No log        | 8.0   | 8    | 0.5328          | 0.6875   |
| No log        | 9.0   | 9    | 0.5325          | 0.6875   |
| 0.5587        | 10.0  | 10   | 0.5320          | 0.6875   |
| 0.5587        | 11.0  | 11   | 0.5314          | 0.6875   |
| 0.5587        | 12.0  | 12   | 0.5305          | 0.6875   |
| 0.5587        | 13.0  | 13   | 0.5296          | 0.6875   |
| 0.5587        | 14.0  | 14   | 0.5285          | 0.6875   |
| 0.5587        | 15.0  | 15   | 0.5274          | 0.6875   |
| 0.5587        | 16.0  | 16   | 0.5264          | 0.6875   |
| 0.5587        | 17.0  | 17   | 0.5254          | 0.6875   |
| 0.5587        | 18.0  | 18   | 0.5244          | 0.6875   |
| 0.5587        | 19.0  | 19   | 0.5235          | 0.6875   |
| 0.5357        | 20.0  | 20   | 0.5225          | 0.6875   |
| 0.5357        | 21.0  | 21   | 0.5216          | 0.6875   |
| 0.5357        | 22.0  | 22   | 0.5204          | 0.6875   |
| 0.5357        | 23.0  | 23   | 0.5192          | 0.6875   |
| 0.5357        | 24.0  | 24   | 0.5179          | 0.6875   |
| 0.5357        | 25.0  | 25   | 0.5165          | 0.6875   |
| 0.5357        | 26.0  | 26   | 0.5151          | 0.7188   |
| 0.5357        | 27.0  | 27   | 0.5135          | 0.7188   |
| 0.5357        | 28.0  | 28   | 0.5119          | 0.7188   |
| 0.5357        | 29.0  | 29   | 0.5102          | 0.7188   |
| 0.4826        | 30.0  | 30   | 0.5085          | 0.7188   |
| 0.4826        | 31.0  | 31   | 0.5064          | 0.7188   |
| 0.4826        | 32.0  | 32   | 0.5050          | 0.7188   |
| 0.4826        | 33.0  | 33   | 0.5036          | 0.7188   |
| 0.4826        | 34.0  | 34   | 0.5019          | 0.7188   |
| 0.4826        | 35.0  | 35   | 0.5002          | 0.7188   |
| 0.4826        | 36.0  | 36   | 0.4980          | 0.7188   |
| 0.4826        | 37.0  | 37   | 0.4958          | 0.7188   |
| 0.4826        | 38.0  | 38   | 0.4931          | 0.7188   |
| 0.4826        | 39.0  | 39   | 0.4900          | 0.7188   |
| 0.438         | 40.0  | 40   | 0.4866          | 0.75     |
| 0.438         | 41.0  | 41   | 0.4831          | 0.75     |
| 0.438         | 42.0  | 42   | 0.4802          | 0.75     |
| 0.438         | 43.0  | 43   | 0.4773          | 0.75     |
| 0.438         | 44.0  | 44   | 0.4746          | 0.75     |
| 0.438         | 45.0  | 45   | 0.4713          | 0.7812   |
| 0.438         | 46.0  | 46   | 0.4685          | 0.7812   |
| 0.438         | 47.0  | 47   | 0.4651          | 0.7812   |
| 0.438         | 48.0  | 48   | 0.4620          | 0.7812   |
| 0.438         | 49.0  | 49   | 0.4583          | 0.7812   |
| 0.367         | 50.0  | 50   | 0.4552          | 0.7812   |
| 0.367         | 51.0  | 51   | 0.4533          | 0.7812   |
| 0.367         | 52.0  | 52   | 0.4519          | 0.7812   |
| 0.367         | 53.0  | 53   | 0.4500          | 0.7812   |
| 0.367         | 54.0  | 54   | 0.4482          | 0.7812   |
| 0.367         | 55.0  | 55   | 0.4470          | 0.7812   |
| 0.367         | 56.0  | 56   | 0.4460          | 0.7812   |
| 0.367         | 57.0  | 57   | 0.4452          | 0.7812   |
| 0.367         | 58.0  | 58   | 0.4440          | 0.7812   |
| 0.367         | 59.0  | 59   | 0.4422          | 0.7812   |
| 0.2811        | 60.0  | 60   | 0.4401          | 0.7812   |
| 0.2811        | 61.0  | 61   | 0.4391          | 0.7812   |
| 0.2811        | 62.0  | 62   | 0.4370          | 0.7812   |
| 0.2811        | 63.0  | 63   | 0.4358          | 0.7812   |
| 0.2811        | 64.0  | 64   | 0.4342          | 0.7812   |
| 0.2811        | 65.0  | 65   | 0.4338          | 0.7812   |
| 0.2811        | 66.0  | 66   | 0.4339          | 0.7812   |
| 0.2811        | 67.0  | 67   | 0.4345          | 0.7812   |
| 0.2811        | 68.0  | 68   | 0.4339          | 0.7812   |
| 0.2811        | 69.0  | 69   | 0.4339          | 0.75     |
| 0.22          | 70.0  | 70   | 0.4347          | 0.7812   |
| 0.22          | 71.0  | 71   | 0.4342          | 0.7812   |
| 0.22          | 72.0  | 72   | 0.4338          | 0.7812   |
| 0.22          | 73.0  | 73   | 0.4335          | 0.7812   |
| 0.22          | 74.0  | 74   | 0.4322          | 0.7812   |
| 0.22          | 75.0  | 75   | 0.4296          | 0.7812   |
| 0.22          | 76.0  | 76   | 0.4266          | 0.8125   |
| 0.22          | 77.0  | 77   | 0.4230          | 0.8438   |
| 0.22          | 78.0  | 78   | 0.4199          | 0.8438   |
| 0.22          | 79.0  | 79   | 0.4170          | 0.8438   |
| 0.1839        | 80.0  | 80   | 0.4147          | 0.8438   |
| 0.1839        | 81.0  | 81   | 0.4131          | 0.8438   |
| 0.1839        | 82.0  | 82   | 0.4120          | 0.8438   |
| 0.1839        | 83.0  | 83   | 0.4102          | 0.8438   |
| 0.1839        | 84.0  | 84   | 0.4090          | 0.8438   |
| 0.1839        | 85.0  | 85   | 0.4073          | 0.8438   |
| 0.1839        | 86.0  | 86   | 0.4059          | 0.8438   |
| 0.1839        | 87.0  | 87   | 0.4049          | 0.8438   |
| 0.1839        | 88.0  | 88   | 0.4043          | 0.8438   |
| 0.1839        | 89.0  | 89   | 0.4044          | 0.8438   |
| 0.1385        | 90.0  | 90   | 0.4045          | 0.8438   |
| 0.1385        | 91.0  | 91   | 0.4049          | 0.8438   |
| 0.1385        | 92.0  | 92   | 0.4054          | 0.8438   |
| 0.1385        | 93.0  | 93   | 0.4059          | 0.8438   |
| 0.1385        | 94.0  | 94   | 0.4057          | 0.8125   |
| 0.1385        | 95.0  | 95   | 0.4066          | 0.8125   |
| 0.1385        | 96.0  | 96   | 0.4070          | 0.8125   |
| 0.1385        | 97.0  | 97   | 0.4072          | 0.8125   |
| 0.1385        | 98.0  | 98   | 0.4078          | 0.8125   |
| 0.1385        | 99.0  | 99   | 0.4081          | 0.8125   |
| 0.1178        | 100.0 | 100  | 0.4079          | 0.8125   |
| 0.1178        | 101.0 | 101  | 0.4083          | 0.8125   |
| 0.1178        | 102.0 | 102  | 0.4087          | 0.8125   |
| 0.1178        | 103.0 | 103  | 0.4101          | 0.8125   |
| 0.1178        | 104.0 | 104  | 0.4120          | 0.8125   |
| 0.1178        | 105.0 | 105  | 0.4132          | 0.8125   |
| 0.1178        | 106.0 | 106  | 0.4148          | 0.8125   |
| 0.1178        | 107.0 | 107  | 0.4163          | 0.8125   |
| 0.1178        | 108.0 | 108  | 0.4176          | 0.8125   |
| 0.1178        | 109.0 | 109  | 0.4207          | 0.8125   |
| 0.0987        | 110.0 | 110  | 0.4235          | 0.8125   |
| 0.0987        | 111.0 | 111  | 0.4253          | 0.8125   |
| 0.0987        | 112.0 | 112  | 0.4268          | 0.8125   |
| 0.0987        | 113.0 | 113  | 0.4273          | 0.8125   |
| 0.0987        | 114.0 | 114  | 0.4271          | 0.8125   |
| 0.0987        | 115.0 | 115  | 0.4270          | 0.8125   |
| 0.0987        | 116.0 | 116  | 0.4277          | 0.8125   |
| 0.0987        | 117.0 | 117  | 0.4279          | 0.8125   |
| 0.0987        | 118.0 | 118  | 0.4287          | 0.8125   |
| 0.0987        | 119.0 | 119  | 0.4264          | 0.8125   |
| 0.0788        | 120.0 | 120  | 0.4252          | 0.8125   |
| 0.0788        | 121.0 | 121  | 0.4234          | 0.8125   |
| 0.0788        | 122.0 | 122  | 0.4213          | 0.8125   |
| 0.0788        | 123.0 | 123  | 0.4184          | 0.8125   |
| 0.0788        | 124.0 | 124  | 0.4164          | 0.8125   |
| 0.0788        | 125.0 | 125  | 0.4148          | 0.8125   |
| 0.0788        | 126.0 | 126  | 0.4140          | 0.8125   |
| 0.0788        | 127.0 | 127  | 0.4142          | 0.8125   |
| 0.0788        | 128.0 | 128  | 0.4135          | 0.8125   |
| 0.0788        | 129.0 | 129  | 0.4132          | 0.8125   |
| 0.0612        | 130.0 | 130  | 0.4131          | 0.8125   |
| 0.0612        | 131.0 | 131  | 0.4136          | 0.8125   |
| 0.0612        | 132.0 | 132  | 0.4144          | 0.8125   |
| 0.0612        | 133.0 | 133  | 0.4148          | 0.8125   |
| 0.0612        | 134.0 | 134  | 0.4154          | 0.8125   |
| 0.0612        | 135.0 | 135  | 0.4167          | 0.8125   |
| 0.0612        | 136.0 | 136  | 0.4181          | 0.8125   |
| 0.0612        | 137.0 | 137  | 0.4199          | 0.8125   |
| 0.0612        | 138.0 | 138  | 0.4211          | 0.8125   |
| 0.0612        | 139.0 | 139  | 0.4222          | 0.8125   |
| 0.0466        | 140.0 | 140  | 0.4243          | 0.8125   |
| 0.0466        | 141.0 | 141  | 0.4256          | 0.8125   |
| 0.0466        | 142.0 | 142  | 0.4278          | 0.8125   |
| 0.0466        | 143.0 | 143  | 0.4280          | 0.8125   |
| 0.0466        | 144.0 | 144  | 0.4286          | 0.8125   |
| 0.0466        | 145.0 | 145  | 0.4294          | 0.8125   |
| 0.0466        | 146.0 | 146  | 0.4311          | 0.8125   |
| 0.0466        | 147.0 | 147  | 0.4332          | 0.8125   |
| 0.0466        | 148.0 | 148  | 0.4351          | 0.7812   |
| 0.0466        | 149.0 | 149  | 0.4371          | 0.7812   |
| 0.036         | 150.0 | 150  | 0.4392          | 0.7812   |


### Framework versions

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