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_padding70model
  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: 0.93036
      name: Accuracy
---

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# distilbert_imdb_padding70model

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: 0.7503
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2385        | 1.0   | 1563  | 0.2404          | 0.9121   |
| 0.1808        | 2.0   | 3126  | 0.2250          | 0.9273   |
| 0.1148        | 3.0   | 4689  | 0.3192          | 0.9253   |
| 0.0711        | 4.0   | 6252  | 0.3479          | 0.9272   |
| 0.0566        | 5.0   | 7815  | 0.4082          | 0.9260   |
| 0.0409        | 6.0   | 9378  | 0.4675          | 0.9268   |
| 0.028         | 7.0   | 10941 | 0.4345          | 0.9268   |
| 0.0209        | 8.0   | 12504 | 0.5870          | 0.9224   |
| 0.0228        | 9.0   | 14067 | 0.4920          | 0.9269   |
| 0.0132        | 10.0  | 15630 | 0.5973          | 0.9248   |
| 0.013         | 11.0  | 17193 | 0.5962          | 0.9282   |
| 0.0127        | 12.0  | 18756 | 0.6695          | 0.9245   |
| 0.0028        | 13.0  | 20319 | 0.7241          | 0.9269   |
| 0.0102        | 14.0  | 21882 | 0.5935          | 0.9298   |
| 0.0033        | 15.0  | 23445 | 0.6654          | 0.9287   |
| 0.0039        | 16.0  | 25008 | 0.6902          | 0.9299   |
| 0.0012        | 17.0  | 26571 | 0.7281          | 0.9281   |
| 0.0023        | 18.0  | 28134 | 0.7369          | 0.9306   |
| 0.0001        | 19.0  | 29697 | 0.7462          | 0.9307   |
| 0.0019        | 20.0  | 31260 | 0.7503          | 0.9304   |


### Framework versions

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