Instructions to use omarmomen/structroberta_sx2_final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use omarmomen/structroberta_sx2_final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="omarmomen/structroberta_sx2_final", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("omarmomen/structroberta_sx2_final", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("omarmomen/structroberta_sx2_final", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
File size: 474 Bytes
35ea748 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"epoch": 10.0,
"eval_accuracy": 0.939230740070343,
"eval_f1": 0.9352989352989353,
"eval_loss": 0.2740771472454071,
"eval_mcc": 0.8850224552110015,
"eval_runtime": 38.415,
"eval_samples": 18200,
"eval_samples_per_second": 473.773,
"eval_steps_per_second": 59.222,
"train_loss": 0.0159600691673787,
"train_runtime": 452.3148,
"train_samples": 9086,
"train_samples_per_second": 200.878,
"train_steps_per_second": 1.68
} |