Instructions to use Realgon/roberta_sst2_padding60model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Realgon/roberta_sst2_padding60model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Realgon/roberta_sst2_padding60model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Realgon/roberta_sst2_padding60model") model = AutoModelForSequenceClassification.from_pretrained("Realgon/roberta_sst2_padding60model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
roberta_sst2_padding60model
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5143
- Accuracy: 0.9445
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 |
|---|---|---|---|---|
| No log | 1.0 | 433 | 0.2571 | 0.9083 |
| 0.3356 | 2.0 | 866 | 0.1977 | 0.9407 |
| 0.1872 | 3.0 | 1299 | 0.2530 | 0.9396 |
| 0.1195 | 4.0 | 1732 | 0.2908 | 0.9434 |
| 0.0754 | 5.0 | 2165 | 0.3693 | 0.9412 |
| 0.043 | 6.0 | 2598 | 0.3650 | 0.9379 |
| 0.0317 | 7.0 | 3031 | 0.4696 | 0.9390 |
| 0.0317 | 8.0 | 3464 | 0.4233 | 0.9434 |
| 0.0277 | 9.0 | 3897 | 0.4518 | 0.9385 |
| 0.0248 | 10.0 | 4330 | 0.4169 | 0.9418 |
| 0.0156 | 11.0 | 4763 | 0.5964 | 0.9325 |
| 0.0116 | 12.0 | 5196 | 0.4787 | 0.9412 |
| 0.0093 | 13.0 | 5629 | 0.4558 | 0.9456 |
| 0.0129 | 14.0 | 6062 | 0.5166 | 0.9330 |
| 0.0129 | 15.0 | 6495 | 0.5489 | 0.9407 |
| 0.0068 | 16.0 | 6928 | 0.5002 | 0.9440 |
| 0.0059 | 17.0 | 7361 | 0.5227 | 0.9445 |
| 0.002 | 18.0 | 7794 | 0.5155 | 0.9462 |
| 0.0032 | 19.0 | 8227 | 0.5027 | 0.9473 |
| 0.0008 | 20.0 | 8660 | 0.5143 | 0.9445 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.1
- Datasets 2.12.0
- Tokenizers 0.13.3
- Downloads last month
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Model tree for Realgon/roberta_sst2_padding60model
Base model
FacebookAI/roberta-base