|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imdb |
|
metrics: |
|
- accuracy |
|
- f1 |
|
model-index: |
|
- name: finetuned-base_mini |
|
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: 0.9076 |
|
- name: F1 |
|
type: f1 |
|
value: 0.9515621723631789 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# finetuned-base_mini |
|
|
|
This model is a fine-tuned version of [google/bert_uncased_L-4_H-256_A-4](https://huggingface.co/google/bert_uncased_L-4_H-256_A-4) on the imdb dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3938 |
|
- Accuracy: 0.9076 |
|
- F1: 0.9516 |
|
|
|
## 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: 3e-05 |
|
- train_batch_size: 128 |
|
- eval_batch_size: 128 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: constant |
|
- num_epochs: 200 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
|
| 0.354 | 2.55 | 500 | 0.2300 | 0.9116 | 0.9538 | |
|
| 0.2086 | 5.1 | 1000 | 0.3182 | 0.8815 | 0.9370 | |
|
| 0.1401 | 7.65 | 1500 | 0.2160 | 0.9241 | 0.9605 | |
|
| 0.0902 | 10.2 | 2000 | 0.4684 | 0.8722 | 0.9317 | |
|
| 0.0654 | 12.76 | 2500 | 0.4885 | 0.8747 | 0.9332 | |
|
| 0.043 | 15.31 | 3000 | 0.3938 | 0.9076 | 0.9516 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.25.0 |
|
- Pytorch 1.12.1+cu113 |
|
- Datasets 2.7.1 |
|
- Tokenizers 0.13.2 |
|
|