transformers 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: left_padding80model
  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: 0.92892
      name: Accuracy
---

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# left_padding80model

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:
- Accuracy: 0.9289
- Loss: 0.7047

## 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: 10

### Training results

| Training Loss | Epoch | Step  | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 0.0355        | 1.0   | 1563  | 0.9217   | 0.5841          |
| 0.0049        | 2.0   | 3126  | 0.9265   | 0.5822          |
| 0.0273        | 3.0   | 4689  | 0.9264   | 0.5829          |
| 0.0186        | 4.0   | 6252  | 0.9261   | 0.6172          |
| 0.0188        | 5.0   | 7815  | 0.9224   | 0.5887          |
| 0.0066        | 6.0   | 9378  | 0.9265   | 0.5949          |
| 0.0           | 7.0   | 10941 | 0.9268   | 0.6716          |
| 0.0024        | 8.0   | 12504 | 0.9284   | 0.6961          |
| 0.0           | 9.0   | 14067 | 0.9267   | 0.7182          |
| 0.0           | 10.0  | 15630 | 0.9289   | 0.7047          |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.0.0+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1
