transformers pytorch distilbert text-classification generated_from_trainer dataset:imdb base_model:distilbert/distilbert-base-uncased base_model:finetune:distilbert/distilbert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: distilbert-base-uncased
datasets:
- imdb
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: N_distilbert_imdb_padding50model
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: imdb
      type: imdb
      config: plain_text
      split: test
      args: plain_text
    metrics:
    - type: accuracy
      value: 0.93268
      name: Accuracy
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 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
