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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: N_distilbert_imdb_padding70model
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: imdb
      type: imdb
      config: plain_text
      split: test
      args: plain_text
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.92932
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# N_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: 0.7329
- Accuracy: 0.9293

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.243         | 1.0   | 1563  | 0.2326          | 0.9132   |
| 0.1814        | 2.0   | 3126  | 0.2110          | 0.9285   |
| 0.1108        | 3.0   | 4689  | 0.3094          | 0.9227   |
| 0.0738        | 4.0   | 6252  | 0.3288          | 0.9263   |
| 0.0487        | 5.0   | 7815  | 0.4211          | 0.9267   |
| 0.0437        | 6.0   | 9378  | 0.4656          | 0.9265   |
| 0.0206        | 7.0   | 10941 | 0.5168          | 0.9272   |
| 0.0271        | 8.0   | 12504 | 0.5283          | 0.9281   |
| 0.0222        | 9.0   | 14067 | 0.5181          | 0.927    |
| 0.0214        | 10.0  | 15630 | 0.5876          | 0.9265   |
| 0.0185        | 11.0  | 17193 | 0.6311          | 0.9264   |
| 0.0099        | 12.0  | 18756 | 0.6656          | 0.927    |
| 0.0084        | 13.0  | 20319 | 0.6685          | 0.9254   |
| 0.0025        | 14.0  | 21882 | 0.7040          | 0.9256   |
| 0.0047        | 15.0  | 23445 | 0.7220          | 0.9295   |
| 0.0041        | 16.0  | 25008 | 0.7185          | 0.9270   |
| 0.0028        | 17.0  | 26571 | 0.7079          | 0.93     |
| 0.0037        | 18.0  | 28134 | 0.7378          | 0.9269   |
| 0.0019        | 19.0  | 29697 | 0.7255          | 0.9288   |
| 0.0001        | 20.0  | 31260 | 0.7329          | 0.9293   |


### Framework versions

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