Instructions to use Realgon/N_bert_twitterfin_padding80model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Realgon/N_bert_twitterfin_padding80model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Realgon/N_bert_twitterfin_padding80model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Realgon/N_bert_twitterfin_padding80model") model = AutoModelForSequenceClassification.from_pretrained("Realgon/N_bert_twitterfin_padding80model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
N_bert_twitterfin_padding80model
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0050
- Accuracy: 0.8894
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6072 | 1.0 | 597 | 0.3449 | 0.8748 |
| 0.3281 | 2.0 | 1194 | 0.3080 | 0.8878 |
| 0.2384 | 3.0 | 1791 | 0.3908 | 0.8894 |
| 0.1552 | 4.0 | 2388 | 0.5590 | 0.8719 |
| 0.1206 | 5.0 | 2985 | 0.6288 | 0.8802 |
| 0.0501 | 6.0 | 3582 | 0.6952 | 0.8874 |
| 0.0357 | 7.0 | 4179 | 0.7691 | 0.8827 |
| 0.0314 | 8.0 | 4776 | 0.8138 | 0.8844 |
| 0.0293 | 9.0 | 5373 | 0.8231 | 0.8886 |
| 0.0199 | 10.0 | 5970 | 0.8076 | 0.8890 |
| 0.0191 | 11.0 | 6567 | 0.8359 | 0.8903 |
| 0.0071 | 12.0 | 7164 | 0.8779 | 0.8857 |
| 0.0105 | 13.0 | 7761 | 0.9540 | 0.8874 |
| 0.0068 | 14.0 | 8358 | 0.9292 | 0.8890 |
| 0.0094 | 15.0 | 8955 | 0.9410 | 0.8903 |
| 0.0065 | 16.0 | 9552 | 0.9804 | 0.8857 |
| 0.0066 | 17.0 | 10149 | 0.9936 | 0.8878 |
| 0.0025 | 18.0 | 10746 | 1.0035 | 0.8915 |
| 0.0038 | 19.0 | 11343 | 1.0173 | 0.8878 |
| 0.0024 | 20.0 | 11940 | 1.0050 | 0.8894 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
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Model tree for Realgon/N_bert_twitterfin_padding80model
Base model
google-bert/bert-base-uncased