Instructions to use Realgon/bert_sst2_padding80model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Realgon/bert_sst2_padding80model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Realgon/bert_sst2_padding80model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Realgon/bert_sst2_padding80model") model = AutoModelForSequenceClassification.from_pretrained("Realgon/bert_sst2_padding80model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
bert_sst2_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: 0.7194
- Accuracy: 0.9226
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 | 0.2350 | 0.9121 |
| 0.3142 | 2.0 | 866 | 0.3585 | 0.9072 |
| 0.1538 | 3.0 | 1299 | 0.4781 | 0.9110 |
| 0.0656 | 4.0 | 1732 | 0.4383 | 0.9132 |
| 0.0366 | 5.0 | 2165 | 0.5503 | 0.9160 |
| 0.0215 | 6.0 | 2598 | 0.7577 | 0.9044 |
| 0.0145 | 7.0 | 3031 | 0.5950 | 0.9187 |
| 0.0145 | 8.0 | 3464 | 0.6371 | 0.9132 |
| 0.012 | 9.0 | 3897 | 0.7315 | 0.9143 |
| 0.0131 | 10.0 | 4330 | 0.6525 | 0.9116 |
| 0.0131 | 11.0 | 4763 | 0.7516 | 0.9061 |
| 0.0082 | 12.0 | 5196 | 0.6153 | 0.9220 |
| 0.0082 | 13.0 | 5629 | 0.6638 | 0.9231 |
| 0.0057 | 14.0 | 6062 | 0.6706 | 0.9182 |
| 0.0057 | 15.0 | 6495 | 0.6851 | 0.9209 |
| 0.0034 | 16.0 | 6928 | 0.7433 | 0.9116 |
| 0.0038 | 17.0 | 7361 | 0.6961 | 0.9237 |
| 0.0026 | 18.0 | 7794 | 0.8033 | 0.9088 |
| 0.0026 | 19.0 | 8227 | 0.6943 | 0.9226 |
| 0.0021 | 20.0 | 8660 | 0.7194 | 0.9226 |
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/bert_sst2_padding80model
Base model
google-bert/bert-base-uncased