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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- ag_news
metrics:
- accuracy
model-index:
- name: distilbert_agnews_padding50model
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: 0.9432894736842106
---
<!-- 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. -->
# distilbert_agnews_padding50model
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the ag_news dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6727
- Accuracy: 0.9433
## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.1828 | 1.0 | 7500 | 0.1902 | 0.94 |
| 0.1398 | 2.0 | 15000 | 0.1989 | 0.9433 |
| 0.1177 | 3.0 | 22500 | 0.2083 | 0.9459 |
| 0.0933 | 4.0 | 30000 | 0.2547 | 0.9439 |
| 0.0648 | 5.0 | 37500 | 0.3024 | 0.9428 |
| 0.0427 | 6.0 | 45000 | 0.3627 | 0.9401 |
| 0.034 | 7.0 | 52500 | 0.4282 | 0.9362 |
| 0.0325 | 8.0 | 60000 | 0.4297 | 0.9404 |
| 0.0217 | 9.0 | 67500 | 0.4508 | 0.9387 |
| 0.0126 | 10.0 | 75000 | 0.4900 | 0.9397 |
| 0.0147 | 11.0 | 82500 | 0.5530 | 0.9399 |
| 0.0103 | 12.0 | 90000 | 0.5293 | 0.9408 |
| 0.0108 | 13.0 | 97500 | 0.5388 | 0.9413 |
| 0.0068 | 14.0 | 105000 | 0.6006 | 0.9397 |
| 0.0028 | 15.0 | 112500 | 0.5974 | 0.9432 |
| 0.005 | 16.0 | 120000 | 0.5617 | 0.9413 |
| 0.0027 | 17.0 | 127500 | 0.6217 | 0.9433 |
| 0.0004 | 18.0 | 135000 | 0.6415 | 0.9420 |
| 0.0011 | 19.0 | 142500 | 0.6566 | 0.9442 |
| 0.0004 | 20.0 | 150000 | 0.6727 | 0.9433 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
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