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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: N_distilbert_imdb_padding50model
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
config: plain_text
split: test
args: plain_text
metrics:
- name: Accuracy
type: accuracy
value: 0.93268
---
<!-- 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_distilbert_imdb_padding50model
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7391
- Accuracy: 0.9327
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2431 | 1.0 | 1563 | 0.2690 | 0.9089 |
| 0.1734 | 2.0 | 3126 | 0.2418 | 0.9260 |
| 0.1167 | 3.0 | 4689 | 0.4345 | 0.9078 |
| 0.0685 | 4.0 | 6252 | 0.3717 | 0.926 |
| 0.0445 | 5.0 | 7815 | 0.4502 | 0.9242 |
| 0.0338 | 6.0 | 9378 | 0.4786 | 0.9287 |
| 0.0293 | 7.0 | 10941 | 0.5332 | 0.9214 |
| 0.0191 | 8.0 | 12504 | 0.5435 | 0.9287 |
| 0.0182 | 9.0 | 14067 | 0.5450 | 0.9265 |
| 0.015 | 10.0 | 15630 | 0.5398 | 0.9297 |
| 0.0122 | 11.0 | 17193 | 0.6565 | 0.9226 |
| 0.0089 | 12.0 | 18756 | 0.6521 | 0.9280 |
| 0.0081 | 13.0 | 20319 | 0.6755 | 0.9285 |
| 0.0067 | 14.0 | 21882 | 0.6753 | 0.93 |
| 0.0054 | 15.0 | 23445 | 0.7014 | 0.9305 |
| 0.0023 | 16.0 | 25008 | 0.7440 | 0.9308 |
| 0.0004 | 17.0 | 26571 | 0.7371 | 0.9286 |
| 0.0 | 18.0 | 28134 | 0.7497 | 0.9302 |
| 0.0004 | 19.0 | 29697 | 0.7386 | 0.9324 |
| 0.0002 | 20.0 | 31260 | 0.7391 | 0.9327 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
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