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---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- ag_news
metrics:
- accuracy
model-index:
- name: N_bert_agnews_padding40model
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: ag_news
type: ag_news
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9473684210526315
---
<!-- 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_agnews_padding40model
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the ag_news dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5661
- Accuracy: 0.9474
## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.1785 | 1.0 | 7500 | 0.1884 | 0.9421 |
| 0.1379 | 2.0 | 15000 | 0.1990 | 0.9478 |
| 0.1127 | 3.0 | 22500 | 0.2389 | 0.9408 |
| 0.0846 | 4.0 | 30000 | 0.2528 | 0.9492 |
| 0.0581 | 5.0 | 37500 | 0.3041 | 0.9436 |
| 0.0456 | 6.0 | 45000 | 0.3415 | 0.9468 |
| 0.0411 | 7.0 | 52500 | 0.4081 | 0.9430 |
| 0.0239 | 8.0 | 60000 | 0.4415 | 0.9433 |
| 0.0202 | 9.0 | 67500 | 0.4380 | 0.9404 |
| 0.0126 | 10.0 | 75000 | 0.4637 | 0.9425 |
| 0.0175 | 11.0 | 82500 | 0.4485 | 0.9455 |
| 0.0126 | 12.0 | 90000 | 0.4761 | 0.9449 |
| 0.0046 | 13.0 | 97500 | 0.5009 | 0.9455 |
| 0.0038 | 14.0 | 105000 | 0.4784 | 0.9482 |
| 0.0035 | 15.0 | 112500 | 0.5282 | 0.9451 |
| 0.0046 | 16.0 | 120000 | 0.5256 | 0.9464 |
| 0.0026 | 17.0 | 127500 | 0.5081 | 0.9501 |
| 0.0008 | 18.0 | 135000 | 0.5543 | 0.9467 |
| 0.0002 | 19.0 | 142500 | 0.5448 | 0.9488 |
| 0.0016 | 20.0 | 150000 | 0.5661 | 0.9474 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
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