---
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: 0703-lr5e-05_warm0.1_epoch6
  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: 0.92816
---

<!-- 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. -->

# 0703-lr5e-05_warm0.1_epoch6

This model is a fine-tuned version of [yujiepan/bert-base-uncased-imdb](https://huggingface.co/yujiepan/bert-base-uncased-imdb) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.53258
- Accuracy: 0.92816

## 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: 5e-05
- train_batch_size: 32
- 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: 6.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.5   | 391  | 0.4331          | 0.9122   |
| 0.0385        | 1.0   | 782  | 0.3080          | 0.9150   |
| 0.0654        | 1.5   | 1173 | 0.3286          | 0.9164   |
| 0.0636        | 2.0   | 1564 | 0.4296          | 0.9184   |
| 0.0636        | 2.5   | 1955 | 0.5366          | 0.9170   |
| 0.0344        | 3.0   | 2346 | 0.4581          | 0.9172   |
| 0.0285        | 3.5   | 2737 | 0.5553          | 0.9164   |
| 0.0163        | 4.0   | 3128 | 0.5055          | 0.9194   |
| 0.0104        | 4.5   | 3519 | 0.5432          | 0.9264   |
| 0.0104        | 5.0   | 3910 | 0.5357          | 0.9268   |
| 0.0034        | 5.5   | 4301 | 0.5457          | 0.9249   |
| 0.0046        | 6.0   | 4692 | 0.5326          | 0.9282   |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.1
- Datasets 2.11.0
- Tokenizers 0.13.3