transformers pytorch bert text-classification generated_from_trainer dataset:imdb base_model:choidf/finetuning-sentiment-model-bert-base-25000-samples base_model:finetune:choidf/finetuning-sentiment-model-bert-base-25000-samples model-index autotrain_compatible endpoints_compatible region:us
---
base_model: choidf/finetuning-sentiment-model-bert-base-25000-samples
datasets:
- imdb
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: finetuning-sentiment-model-bert-base-25000-samples
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: imdb
      type: imdb
      config: plain_text
      split: train
      args: plain_text
    metrics:
    - type: accuracy
      value: 0.9308
      name: Accuracy
    - type: f1
      value: 0.9325009754194303
      name: F1
---

<!-- 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. -->

# finetuning-sentiment-model-bert-base-25000-samples

This model is a fine-tuned version of [choidf/finetuning-sentiment-model-bert-base-25000-samples](https://huggingface.co/choidf/finetuning-sentiment-model-bert-base-25000-samples) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5129
- Accuracy: 0.9308
- F1: 0.9325

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.0535        | 1.0   | 1407 | 0.4188          | 0.9224   | 0.9222 |
| 0.0324        | 2.0   | 2814 | 0.4382          | 0.928    | 0.9288 |
| 0.0201        | 3.0   | 4221 | 0.4542          | 0.928    | 0.9308 |
| 0.0202        | 4.0   | 5628 | 0.4747          | 0.9296   | 0.9321 |
| 0.0057        | 5.0   | 7035 | 0.5129          | 0.9308   | 0.9325 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
