transformers pytorch tensorboard safetensors 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: distilbert_imdb_padding10model
  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: 0.93364
      name: Accuracy
---

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# 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: 0.6898
- Accuracy: 0.9336

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2352        | 1.0   | 1563  | 0.2181          | 0.9211   |
| 0.1717        | 2.0   | 3126  | 0.2141          | 0.9301   |
| 0.1043        | 3.0   | 4689  | 0.2965          | 0.9269   |
| 0.0652        | 4.0   | 6252  | 0.3615          | 0.9291   |
| 0.044         | 5.0   | 7815  | 0.4307          | 0.9279   |
| 0.0368        | 6.0   | 9378  | 0.5081          | 0.9253   |
| 0.0198        | 7.0   | 10941 | 0.4579          | 0.928    |
| 0.0258        | 8.0   | 12504 | 0.5307          | 0.9271   |
| 0.0154        | 9.0   | 14067 | 0.5795          | 0.9262   |
| 0.0154        | 10.0  | 15630 | 0.6031          | 0.9242   |
| 0.0074        | 11.0  | 17193 | 0.6427          | 0.9289   |
| 0.0085        | 12.0  | 18756 | 0.6715          | 0.9291   |
| 0.007         | 13.0  | 20319 | 0.6645          | 0.9291   |
| 0.0047        | 14.0  | 21882 | 0.6918          | 0.9294   |
| 0.0022        | 15.0  | 23445 | 0.7447          | 0.9304   |
| 0.0032        | 16.0  | 25008 | 0.7146          | 0.9329   |
| 0.004         | 17.0  | 26571 | 0.7050          | 0.9324   |
| 0.0027        | 18.0  | 28134 | 0.6860          | 0.9340   |
| 0.0031        | 19.0  | 29697 | 0.6935          | 0.9330   |
| 0.0004        | 20.0  | 31260 | 0.6898          | 0.9336   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
