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