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---
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
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