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: N_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: 0.93352
      name: Accuracy
---

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# N_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: 0.7558
- Accuracy: 0.9335

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2364        | 1.0   | 1563  | 0.2100          | 0.9252   |
| 0.1754        | 2.0   | 3126  | 0.2253          | 0.928    |
| 0.1006        | 3.0   | 4689  | 0.2885          | 0.9287   |
| 0.0627        | 4.0   | 6252  | 0.3760          | 0.9271   |
| 0.0436        | 5.0   | 7815  | 0.4199          | 0.9281   |
| 0.0353        | 6.0   | 9378  | 0.4874          | 0.9294   |
| 0.0176        | 7.0   | 10941 | 0.6403          | 0.919    |
| 0.0172        | 8.0   | 12504 | 0.5783          | 0.9264   |
| 0.0206        | 9.0   | 14067 | 0.5343          | 0.9298   |
| 0.0125        | 10.0  | 15630 | 0.6186          | 0.927    |
| 0.012         | 11.0  | 17193 | 0.5948          | 0.9309   |
| 0.0094        | 12.0  | 18756 | 0.6524          | 0.9293   |
| 0.0095        | 13.0  | 20319 | 0.6730          | 0.9262   |
| 0.0053        | 14.0  | 21882 | 0.6670          | 0.9316   |
| 0.0024        | 15.0  | 23445 | 0.6873          | 0.9322   |
| 0.0028        | 16.0  | 25008 | 0.6858          | 0.9328   |
| 0.0007        | 17.0  | 26571 | 0.7114          | 0.9326   |
| 0.0014        | 18.0  | 28134 | 0.7477          | 0.9331   |
| 0.0           | 19.0  | 29697 | 0.7567          | 0.9335   |
| 0.0           | 20.0  | 31260 | 0.7558          | 0.9335   |


### Framework versions

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