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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_padding10model
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: 0.93352
---
<!-- 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_padding10model
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: 0.7558
- Accuracy: 0.9335
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2364 | 1.0 | 1563 | 0.2100 | 0.9252 |
| 0.1754 | 2.0 | 3126 | 0.2253 | 0.928 |
| 0.1006 | 3.0 | 4689 | 0.2885 | 0.9287 |
| 0.0627 | 4.0 | 6252 | 0.3760 | 0.9271 |
| 0.0436 | 5.0 | 7815 | 0.4199 | 0.9281 |
| 0.0353 | 6.0 | 9378 | 0.4874 | 0.9294 |
| 0.0176 | 7.0 | 10941 | 0.6403 | 0.919 |
| 0.0172 | 8.0 | 12504 | 0.5783 | 0.9264 |
| 0.0206 | 9.0 | 14067 | 0.5343 | 0.9298 |
| 0.0125 | 10.0 | 15630 | 0.6186 | 0.927 |
| 0.012 | 11.0 | 17193 | 0.5948 | 0.9309 |
| 0.0094 | 12.0 | 18756 | 0.6524 | 0.9293 |
| 0.0095 | 13.0 | 20319 | 0.6730 | 0.9262 |
| 0.0053 | 14.0 | 21882 | 0.6670 | 0.9316 |
| 0.0024 | 15.0 | 23445 | 0.6873 | 0.9322 |
| 0.0028 | 16.0 | 25008 | 0.6858 | 0.9328 |
| 0.0007 | 17.0 | 26571 | 0.7114 | 0.9326 |
| 0.0014 | 18.0 | 28134 | 0.7477 | 0.9331 |
| 0.0 | 19.0 | 29697 | 0.7567 | 0.9335 |
| 0.0 | 20.0 | 31260 | 0.7558 | 0.9335 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
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