Text Classification
Transformers
PyTorch
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use Elron/deberta-v3-large-irony with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Elron/deberta-v3-large-irony with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Elron/deberta-v3-large-irony")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Elron/deberta-v3-large-irony") model = AutoModelForSequenceClassification.from_pretrained("Elron/deberta-v3-large-irony", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 402 Bytes
27e031e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"epoch": 9.99,
"eval_accuracy": 0.7675392627716064,
"eval_loss": 0.7672834396362305,
"eval_runtime": 6.3297,
"eval_samples": 955,
"eval_samples_per_second": 150.876,
"eval_steps_per_second": 9.479,
"train_loss": 0.33834649632486063,
"train_runtime": 677.9414,
"train_samples": 2862,
"train_samples_per_second": 42.216,
"train_steps_per_second": 1.313
} |