transformers tensorboard safetensors distilbert text-classification generated_from_trainer en 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
language:
- en
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: imdb_distilbert-base-uncased
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: imdb
      type: imdb
      config: plain_text
      split: test
      args: imdb
    metrics:
    - type: accuracy
      value: 0.87736
      name: Accuracy
---

<!-- 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. -->

# imdb_distilbert-base-uncased

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: 0.2911
- Accuracy: 0.8774

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6487        | 0.2   | 78   | 0.4402          | 0.8117   |
| 0.402         | 0.4   | 156  | 0.3563          | 0.8416   |
| 0.3528        | 0.6   | 234  | 0.3522          | 0.8434   |
| 0.3362        | 0.8   | 312  | 0.3099          | 0.8652   |
| 0.3184        | 1.0   | 390  | 0.3028          | 0.8700   |
| 0.265         | 1.2   | 468  | 0.3052          | 0.8738   |
| 0.2593        | 1.4   | 546  | 0.2983          | 0.8735   |
| 0.2537        | 1.6   | 624  | 0.2977          | 0.8754   |
| 0.2558        | 1.8   | 702  | 0.2911          | 0.8774   |
| 0.2476        | 1.99  | 780  | 0.2907          | 0.8751   |
| 0.1941        | 2.19  | 858  | 0.3151          | 0.8774   |
| 0.1873        | 2.39  | 936  | 0.3104          | 0.8764   |
| 0.1869        | 2.59  | 1014 | 0.3181          | 0.8771   |
| 0.1807        | 2.79  | 1092 | 0.3148          | 0.8764   |
| 0.1967        | 2.99  | 1170 | 0.3141          | 0.8766   |


### Framework versions

- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
