---
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: 0.6710
- Accuracy: 0.7188

## 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    | 0.6895          | 0.5312   |
| No log        | 2.0   | 2    | 0.6895          | 0.5312   |
| No log        | 3.0   | 3    | 0.6894          | 0.5312   |
| No log        | 4.0   | 4    | 0.6894          | 0.5312   |
| No log        | 5.0   | 5    | 0.6894          | 0.5312   |
| No log        | 6.0   | 6    | 0.6893          | 0.5312   |
| No log        | 7.0   | 7    | 0.6893          | 0.5312   |
| No log        | 8.0   | 8    | 0.6892          | 0.5312   |
| No log        | 9.0   | 9    | 0.6891          | 0.5312   |
| 0.7006        | 10.0  | 10   | 0.6890          | 0.5312   |
| 0.7006        | 11.0  | 11   | 0.6889          | 0.5312   |
| 0.7006        | 12.0  | 12   | 0.6888          | 0.5312   |
| 0.7006        | 13.0  | 13   | 0.6887          | 0.5312   |
| 0.7006        | 14.0  | 14   | 0.6886          | 0.5312   |
| 0.7006        | 15.0  | 15   | 0.6884          | 0.5312   |
| 0.7006        | 16.0  | 16   | 0.6883          | 0.5312   |
| 0.7006        | 17.0  | 17   | 0.6881          | 0.5312   |
| 0.7006        | 18.0  | 18   | 0.6879          | 0.5312   |
| 0.7006        | 19.0  | 19   | 0.6877          | 0.5312   |
| 0.6992        | 20.0  | 20   | 0.6875          | 0.5312   |
| 0.6992        | 21.0  | 21   | 0.6872          | 0.5312   |
| 0.6992        | 22.0  | 22   | 0.6870          | 0.5312   |
| 0.6992        | 23.0  | 23   | 0.6867          | 0.5      |
| 0.6992        | 24.0  | 24   | 0.6864          | 0.5      |
| 0.6992        | 25.0  | 25   | 0.6861          | 0.5      |
| 0.6992        | 26.0  | 26   | 0.6857          | 0.5      |
| 0.6992        | 27.0  | 27   | 0.6854          | 0.5      |
| 0.6992        | 28.0  | 28   | 0.6850          | 0.5      |
| 0.6992        | 29.0  | 29   | 0.6846          | 0.5      |
| 0.68          | 30.0  | 30   | 0.6842          | 0.5      |
| 0.68          | 31.0  | 31   | 0.6838          | 0.5      |
| 0.68          | 32.0  | 32   | 0.6833          | 0.5      |
| 0.68          | 33.0  | 33   | 0.6829          | 0.5      |
| 0.68          | 34.0  | 34   | 0.6824          | 0.5      |
| 0.68          | 35.0  | 35   | 0.6819          | 0.5      |
| 0.68          | 36.0  | 36   | 0.6814          | 0.5312   |
| 0.68          | 37.0  | 37   | 0.6808          | 0.5625   |
| 0.68          | 38.0  | 38   | 0.6802          | 0.5625   |
| 0.68          | 39.0  | 39   | 0.6796          | 0.5938   |
| 0.6655        | 40.0  | 40   | 0.6789          | 0.5938   |
| 0.6655        | 41.0  | 41   | 0.6783          | 0.5938   |
| 0.6655        | 42.0  | 42   | 0.6776          | 0.5938   |
| 0.6655        | 43.0  | 43   | 0.6769          | 0.6562   |
| 0.6655        | 44.0  | 44   | 0.6762          | 0.7188   |
| 0.6655        | 45.0  | 45   | 0.6754          | 0.7188   |
| 0.6655        | 46.0  | 46   | 0.6746          | 0.7188   |
| 0.6655        | 47.0  | 47   | 0.6737          | 0.75     |
| 0.6655        | 48.0  | 48   | 0.6728          | 0.75     |
| 0.6655        | 49.0  | 49   | 0.6719          | 0.75     |
| 0.6452        | 50.0  | 50   | 0.6710          | 0.7188   |


### Framework versions

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