metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: modlee_transformer
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: 0.94184
- name: F1
type: f1
value:
f1: 0.9419838799776555
modlee_transformer
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: 0.2170
- Accuracy: {'accuracy': 0.94184}
- F1: {'f1': 0.9419838799776555}
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.2079 | 1.0 | 1563 | 0.2379 | {'accuracy': 0.9226} | {'f1': 0.9261929282526605} |
| 0.1382 | 2.0 | 3126 | 0.2170 | {'accuracy': 0.94184} | {'f1': 0.9419838799776555} |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3