Instructions to use Realgon/N_roberta_twitterfin_padding10model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Realgon/N_roberta_twitterfin_padding10model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Realgon/N_roberta_twitterfin_padding10model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Realgon/N_roberta_twitterfin_padding10model") model = AutoModelForSequenceClassification.from_pretrained("Realgon/N_roberta_twitterfin_padding10model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
N_roberta_twitterfin_padding10model
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8928
- Accuracy: 0.9041
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 |
|---|---|---|---|---|
| 0.5357 | 1.0 | 597 | 0.3076 | 0.8899 |
| 0.2981 | 2.0 | 1194 | 0.2893 | 0.8920 |
| 0.256 | 3.0 | 1791 | 0.3286 | 0.8924 |
| 0.1801 | 4.0 | 2388 | 0.4796 | 0.8978 |
| 0.1503 | 5.0 | 2985 | 0.5024 | 0.9008 |
| 0.0803 | 6.0 | 3582 | 0.5620 | 0.8974 |
| 0.0729 | 7.0 | 4179 | 0.7456 | 0.8869 |
| 0.0554 | 8.0 | 4776 | 0.7191 | 0.8936 |
| 0.056 | 9.0 | 5373 | 0.6453 | 0.9070 |
| 0.0429 | 10.0 | 5970 | 0.7056 | 0.9028 |
| 0.0291 | 11.0 | 6567 | 0.7841 | 0.8982 |
| 0.025 | 12.0 | 7164 | 0.8934 | 0.8941 |
| 0.0176 | 13.0 | 7761 | 0.7528 | 0.9058 |
| 0.0191 | 14.0 | 8358 | 0.8226 | 0.8987 |
| 0.0201 | 15.0 | 8955 | 0.8367 | 0.9003 |
| 0.0135 | 16.0 | 9552 | 0.8616 | 0.9037 |
| 0.0068 | 17.0 | 10149 | 0.8865 | 0.9016 |
| 0.0089 | 18.0 | 10746 | 0.8481 | 0.9070 |
| 0.0054 | 19.0 | 11343 | 0.8897 | 0.9045 |
| 0.0075 | 20.0 | 11940 | 0.8928 | 0.9041 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
- Downloads last month
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Model tree for Realgon/N_roberta_twitterfin_padding10model
Base model
FacebookAI/roberta-base