Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use reginandcrabbe/Roberta-Sentiment-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use reginandcrabbe/Roberta-Sentiment-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="reginandcrabbe/Roberta-Sentiment-Classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("reginandcrabbe/Roberta-Sentiment-Classifier") model = AutoModelForSequenceClassification.from_pretrained("reginandcrabbe/Roberta-Sentiment-Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Roberta-Sentiment-Classifier
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6541
- Accuracy: 0.7619
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.827 | 0.5 | 500 | 0.7463 | 0.7268 |
| 0.7122 | 1.0 | 1000 | 0.6541 | 0.7619 |
| 0.5935 | 1.5 | 1500 | 0.6994 | 0.7654 |
| 0.6097 | 2.0 | 2000 | 0.6578 | 0.7729 |
| 0.4835 | 2.51 | 2500 | 0.7130 | 0.7704 |
| 0.5024 | 3.01 | 3000 | 0.7050 | 0.7719 |
| 0.4045 | 3.51 | 3500 | 0.8216 | 0.7734 |
| 0.4103 | 4.01 | 4000 | 0.8049 | 0.7799 |
| 0.3367 | 4.51 | 4500 | 0.8993 | 0.7779 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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Model tree for reginandcrabbe/Roberta-Sentiment-Classifier
Base model
FacebookAI/roberta-base