Text Classification
Transformers
Safetensors
English
deberta-v2
multilabel-classification
deberta-v3
opp115
text-embeddings-inference
Instructions to use Hacktrix-121/deberta-v3-base-opp115-multilabel-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hacktrix-121/deberta-v3-base-opp115-multilabel-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Hacktrix-121/deberta-v3-base-opp115-multilabel-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Hacktrix-121/deberta-v3-base-opp115-multilabel-v2") model = AutoModelForSequenceClassification.from_pretrained("Hacktrix-121/deberta-v3-base-opp115-multilabel-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload metrics.json with huggingface_hub
Browse files- metrics.json +7 -0
metrics.json
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"macro_f1": 0.8092093641188033,
|
| 3 |
+
"micro_f1": 0.8564516129032258,
|
| 4 |
+
"weighted_f1": 0.8531479321146159,
|
| 5 |
+
"macro_precision": 0.8656589880624014,
|
| 6 |
+
"macro_recall": 0.7697425663813912
|
| 7 |
+
}
|