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-4800-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: 0.9122649070746451
ag-news-twitter-4800-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: 0.9123
- Acc: 0.9126
- Loss: 0.6235
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 |
|---|---|---|---|---|---|
| No log | 1.0 | 300 | 0.8951 | 0.8955 | 0.3460 |
| 0.6828 | 2.0 | 600 | 0.8957 | 0.8959 | 0.3295 |
| 0.6828 | 3.0 | 900 | 0.9096 | 0.9095 | 0.3196 |
| 0.1866 | 4.0 | 1200 | 0.9011 | 0.9018 | 0.4358 |
| 0.0804 | 5.0 | 1500 | 0.9116 | 0.9116 | 0.4441 |
| 0.0804 | 6.0 | 1800 | 0.9121 | 0.9124 | 0.4983 |
| 0.0236 | 7.0 | 2100 | 0.9126 | 0.9128 | 0.5473 |
| 0.0236 | 8.0 | 2400 | 0.9082 | 0.9086 | 0.6025 |
| 0.0092 | 9.0 | 2700 | 0.9121 | 0.9124 | 0.6057 |
| 0.0028 | 10.0 | 3000 | 0.9123 | 0.9126 | 0.6235 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1