metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- ag_news
metrics:
- f1
model-index:
- name: ag-news-twitter-76800-bert-base-uncased
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: ag_news
type: ag_news
config: default
split: test
args: default
metrics:
- name: F1
type: f1
value: 0.9414991482921289
ag-news-twitter-76800-bert-base-uncased
This model is a fine-tuned version of bert-base-uncased on the ag_news dataset. It achieves the following results on the evaluation set:
- F1: 0.9415
- Acc: 0.9416
- Loss: 0.5192
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | F1 | Acc | Validation Loss |
|---|---|---|---|---|---|
| 0.2328 | 1.0 | 4800 | 0.9289 | 0.9289 | 0.2082 |
| 0.2061 | 2.0 | 9600 | 0.9366 | 0.9367 | 0.2154 |
| 0.1488 | 3.0 | 14400 | 0.9401 | 0.9401 | 0.2181 |
| 0.114 | 4.0 | 19200 | 0.9280 | 0.9275 | 0.3199 |
| 0.0818 | 5.0 | 24000 | 0.9399 | 0.94 | 0.2953 |
| 0.051 | 6.0 | 28800 | 0.9402 | 0.9403 | 0.3828 |
| 0.0413 | 7.0 | 33600 | 0.9404 | 0.9403 | 0.4327 |
| 0.0342 | 8.0 | 38400 | 0.9395 | 0.9395 | 0.4291 |
| 0.0192 | 9.0 | 43200 | 0.9422 | 0.9422 | 0.4170 |
| 0.0204 | 10.0 | 48000 | 0.9374 | 0.9374 | 0.4761 |
| 0.0125 | 11.0 | 52800 | 0.9358 | 0.9359 | 0.5126 |
| 0.0124 | 12.0 | 57600 | 0.9415 | 0.9416 | 0.5192 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1