Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use anpmts/bert-sentiment-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anpmts/bert-sentiment-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anpmts/bert-sentiment-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anpmts/bert-sentiment-classifier") model = AutoModelForSequenceClassification.from_pretrained("anpmts/bert-sentiment-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 436 Bytes
c819893 6b710db c819893 6b710db c819893 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"epoch": 10.0,
"eval_accuracy": 0.9736184171050263,
"eval_f1": 0.9736184057853046,
"eval_f1_negative": 0.973601124804235,
"eval_f1_neutral": 0.973635686766374,
"eval_f1_positive": 0.0,
"eval_loss": 0.0820448026061058,
"eval_precision": 0.9736191924477628,
"eval_recall": 0.9736184043929482,
"eval_runtime": 156.7418,
"eval_samples_per_second": 2551.815,
"eval_steps_per_second": 4.989
} |