---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: N_bert_sst5_padding80model
  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. -->

# N_bert_sst5_padding80model

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: 4.1055
- Accuracy: 0.5335

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3295        | 1.0   | 534   | 1.2788          | 0.4231   |
| 1.0046        | 2.0   | 1068  | 1.1005          | 0.5362   |
| 0.7632        | 3.0   | 1602  | 1.1567          | 0.5357   |
| 0.588         | 4.0   | 2136  | 1.4030          | 0.5308   |
| 0.4198        | 5.0   | 2670  | 1.6242          | 0.5244   |
| 0.3036        | 6.0   | 3204  | 1.8412          | 0.5385   |
| 0.222         | 7.0   | 3738  | 2.2298          | 0.5299   |
| 0.1677        | 8.0   | 4272  | 2.4165          | 0.5376   |
| 0.1407        | 9.0   | 4806  | 2.7191          | 0.5285   |
| 0.1199        | 10.0  | 5340  | 3.1297          | 0.5226   |
| 0.0916        | 11.0  | 5874  | 3.3297          | 0.5466   |
| 0.0716        | 12.0  | 6408  | 3.4776          | 0.5385   |
| 0.0717        | 13.0  | 6942  | 3.6198          | 0.5339   |
| 0.047         | 14.0  | 7476  | 3.7826          | 0.5376   |
| 0.0322        | 15.0  | 8010  | 3.8744          | 0.5294   |
| 0.0268        | 16.0  | 8544  | 4.0318          | 0.5145   |
| 0.0204        | 17.0  | 9078  | 4.0118          | 0.5380   |
| 0.0201        | 18.0  | 9612  | 4.0902          | 0.5308   |
| 0.0149        | 19.0  | 10146 | 4.0749          | 0.5357   |
| 0.012         | 20.0  | 10680 | 4.1055          | 0.5335   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3