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_padding40model
  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: 0.93044
      name: Accuracy
---

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# distilbert_imdb_padding40model

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: 0.7661
- Accuracy: 0.9304

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.237         | 1.0   | 1563  | 0.2751          | 0.8951   |
| 0.1699        | 2.0   | 3126  | 0.2169          | 0.9289   |
| 0.1143        | 3.0   | 4689  | 0.3155          | 0.9232   |
| 0.0728        | 4.0   | 6252  | 0.3584          | 0.9266   |
| 0.0396        | 5.0   | 7815  | 0.4750          | 0.9234   |
| 0.0359        | 6.0   | 9378  | 0.5132          | 0.9194   |
| 0.0206        | 7.0   | 10941 | 0.4754          | 0.9283   |
| 0.0252        | 8.0   | 12504 | 0.5639          | 0.9235   |
| 0.0168        | 9.0   | 14067 | 0.5000          | 0.9281   |
| 0.0153        | 10.0  | 15630 | 0.5634          | 0.9283   |
| 0.0105        | 11.0  | 17193 | 0.6007          | 0.9303   |
| 0.0093        | 12.0  | 18756 | 0.6327          | 0.9277   |
| 0.0051        | 13.0  | 20319 | 0.7021          | 0.9268   |
| 0.0035        | 14.0  | 21882 | 0.6893          | 0.9290   |
| 0.0061        | 15.0  | 23445 | 0.7048          | 0.9300   |
| 0.002         | 16.0  | 25008 | 0.7754          | 0.9294   |
| 0.0032        | 17.0  | 26571 | 0.7550          | 0.9297   |
| 0.0006        | 18.0  | 28134 | 0.7681          | 0.9304   |
| 0.0006        | 19.0  | 29697 | 0.7683          | 0.9303   |
| 0.0017        | 20.0  | 31260 | 0.7661          | 0.9304   |


### Framework versions

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