metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: bert-base-uncased-finetuned-imdb
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:
accuracy: 0.94124
- name: F1
type: f1
value:
f1: 0.9412364248240864
bert-base-uncased-finetuned-imdb
This model is a fine-tuned version of bert-base-uncased on the imdb dataset. It achieves the following results on the evaluation set:
- Loss: 0.2708
- Accuracy: {'accuracy': 0.94124}
- F1: {'f1': 0.9412364248240864}
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.2201 | 1.0 | 1563 | 0.2556 | {'accuracy': 0.91716} | {'f1': 0.9168776701523282} |
| 0.1445 | 2.0 | 3126 | 0.2199 | {'accuracy': 0.94092} | {'f1': 0.940911994189728} |
| 0.0719 | 3.0 | 4689 | 0.2708 | {'accuracy': 0.94124} | {'f1': 0.9412364248240864} |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3