metadata
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
finetuned-base_mini
This model is a fine-tuned version of 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