license: apache-2.0 | |
tags: | |
- generated_from_trainer | |
datasets: | |
- imdb | |
metrics: | |
- accuracy | |
- f1 | |
base_model: google/bert_uncased_L-4_H-256_A-4 | |
model-index: | |
- name: finetuned-base_mini | |
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: 0.9076 | |
name: Accuracy | |
- type: f1 | |
value: 0.9515621723631789 | |
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. --> | |
# 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 | |