Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use miguelpr/roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use miguelpr/roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="miguelpr/roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("miguelpr/roberta-base") model = AutoModelForSequenceClassification.from_pretrained("miguelpr/roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 424 Bytes
01806c7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"epoch": 2.0,
"eval_accuracy": 0.645,
"eval_loss": 1.2481324672698975,
"eval_runtime": 12.9479,
"eval_samples": 400,
"eval_samples_per_second": 30.893,
"eval_steps_per_second": 1.004,
"total_flos": 841955377152000.0,
"train_loss": 0.7585713958740234,
"train_runtime": 297.7415,
"train_samples": 1600,
"train_samples_per_second": 10.748,
"train_steps_per_second": 0.672
} |