---
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: 0.6655
- Accuracy: 0.5938

## 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: 2e-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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1    | 0.7052          | 0.5312   |
| No log        | 2.0   | 2    | 0.7051          | 0.5312   |
| No log        | 3.0   | 3    | 0.7050          | 0.5312   |
| No log        | 4.0   | 4    | 0.7048          | 0.5312   |
| No log        | 5.0   | 5    | 0.7045          | 0.5312   |
| No log        | 6.0   | 6    | 0.7042          | 0.5312   |
| No log        | 7.0   | 7    | 0.7038          | 0.5312   |
| No log        | 8.0   | 8    | 0.7034          | 0.5312   |
| No log        | 9.0   | 9    | 0.7029          | 0.5312   |
| 0.7492        | 10.0  | 10   | 0.7023          | 0.5312   |
| 0.7492        | 11.0  | 11   | 0.7017          | 0.5312   |
| 0.7492        | 12.0  | 12   | 0.7010          | 0.5312   |
| 0.7492        | 13.0  | 13   | 0.7002          | 0.5312   |
| 0.7492        | 14.0  | 14   | 0.6994          | 0.5312   |
| 0.7492        | 15.0  | 15   | 0.6985          | 0.5312   |
| 0.7492        | 16.0  | 16   | 0.6976          | 0.5312   |
| 0.7492        | 17.0  | 17   | 0.6966          | 0.5312   |
| 0.7492        | 18.0  | 18   | 0.6956          | 0.5312   |
| 0.7492        | 19.0  | 19   | 0.6946          | 0.5312   |
| 0.7304        | 20.0  | 20   | 0.6935          | 0.5312   |
| 0.7304        | 21.0  | 21   | 0.6924          | 0.5      |
| 0.7304        | 22.0  | 22   | 0.6912          | 0.5625   |
| 0.7304        | 23.0  | 23   | 0.6900          | 0.5625   |
| 0.7304        | 24.0  | 24   | 0.6887          | 0.5625   |
| 0.7304        | 25.0  | 25   | 0.6875          | 0.5625   |
| 0.7304        | 26.0  | 26   | 0.6861          | 0.5625   |
| 0.7304        | 27.0  | 27   | 0.6849          | 0.5625   |
| 0.7304        | 28.0  | 28   | 0.6836          | 0.5625   |
| 0.7304        | 29.0  | 29   | 0.6823          | 0.5625   |
| 0.6885        | 30.0  | 30   | 0.6812          | 0.5938   |
| 0.6885        | 31.0  | 31   | 0.6800          | 0.5625   |
| 0.6885        | 32.0  | 32   | 0.6789          | 0.5625   |
| 0.6885        | 33.0  | 33   | 0.6779          | 0.5312   |
| 0.6885        | 34.0  | 34   | 0.6772          | 0.5312   |
| 0.6885        | 35.0  | 35   | 0.6763          | 0.5312   |
| 0.6885        | 36.0  | 36   | 0.6753          | 0.5625   |
| 0.6885        | 37.0  | 37   | 0.6744          | 0.5625   |
| 0.6885        | 38.0  | 38   | 0.6734          | 0.5938   |
| 0.6885        | 39.0  | 39   | 0.6724          | 0.5938   |
| 0.6578        | 40.0  | 40   | 0.6715          | 0.625    |
| 0.6578        | 41.0  | 41   | 0.6707          | 0.5938   |
| 0.6578        | 42.0  | 42   | 0.6699          | 0.625    |
| 0.6578        | 43.0  | 43   | 0.6692          | 0.625    |
| 0.6578        | 44.0  | 44   | 0.6686          | 0.6562   |
| 0.6578        | 45.0  | 45   | 0.6681          | 0.6562   |
| 0.6578        | 46.0  | 46   | 0.6679          | 0.6562   |
| 0.6578        | 47.0  | 47   | 0.6677          | 0.5938   |
| 0.6578        | 48.0  | 48   | 0.6673          | 0.5938   |
| 0.6578        | 49.0  | 49   | 0.6665          | 0.5938   |
| 0.5964        | 50.0  | 50   | 0.6655          | 0.5938   |


### Framework versions

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