Token Classification
Transformers
Safetensors
PyTorch
Baluchi
xlm-roberta
part-of-speech
pos-tagging
balochi
low-resource
universal-dependencies
shahbakhsh
Eval Results (legacy)
Instructions to use shahbakhsh/BalPOS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shahbakhsh/BalPOS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="shahbakhsh/BalPOS")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("shahbakhsh/BalPOS") model = AutoModelForTokenClassification.from_pretrained("shahbakhsh/BalPOS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "ADJ": { | |
| "precision": 0.785, | |
| "recall": 0.8092783505154639, | |
| "f1-score": 0.7969543147208121, | |
| "support": 194.0 | |
| }, | |
| "ADP": { | |
| "precision": 0.9516616314199395, | |
| "recall": 0.9603658536585366, | |
| "f1-score": 0.9559939301972686, | |
| "support": 328.0 | |
| }, | |
| "ADV": { | |
| "precision": 0.7555555555555555, | |
| "recall": 0.7157894736842105, | |
| "f1-score": 0.7351351351351352, | |
| "support": 95.0 | |
| }, | |
| "AUX": { | |
| "precision": 0.9166666666666666, | |
| "recall": 0.8918918918918919, | |
| "f1-score": 0.9041095890410958, | |
| "support": 148.0 | |
| }, | |
| "CCONJ": { | |
| "precision": 0.9433962264150944, | |
| "recall": 1.0, | |
| "f1-score": 0.970873786407767, | |
| "support": 100.0 | |
| }, | |
| "DET": { | |
| "precision": 0.8152173913043478, | |
| "recall": 0.8064516129032258, | |
| "f1-score": 0.8108108108108109, | |
| "support": 93.0 | |
| }, | |
| "INTJ": { | |
| "precision": 0.0, | |
| "recall": 0.0, | |
| "f1-score": 0.0, | |
| "support": 1.0 | |
| }, | |
| "NOUN": { | |
| "precision": 0.9197530864197531, | |
| "recall": 0.8882265275707899, | |
| "f1-score": 0.9037149355572404, | |
| "support": 671.0 | |
| }, | |
| "NUM": { | |
| "precision": 0.7894736842105263, | |
| "recall": 0.8823529411764706, | |
| "f1-score": 0.8333333333333334, | |
| "support": 17.0 | |
| }, | |
| "PART": { | |
| "precision": 0.8723404255319149, | |
| "recall": 0.6507936507936508, | |
| "f1-score": 0.7454545454545455, | |
| "support": 63.0 | |
| }, | |
| "PRON": { | |
| "precision": 0.9101123595505618, | |
| "recall": 0.9101123595505618, | |
| "f1-score": 0.9101123595505618, | |
| "support": 178.0 | |
| }, | |
| "PROPN": { | |
| "precision": 0.7681159420289855, | |
| "recall": 0.8833333333333333, | |
| "f1-score": 0.8217054263565892, | |
| "support": 60.0 | |
| }, | |
| "PUNCT": { | |
| "precision": 0.9680851063829787, | |
| "recall": 0.994535519125683, | |
| "f1-score": 0.9811320754716981, | |
| "support": 183.0 | |
| }, | |
| "SCONJ": { | |
| "precision": 0.921875, | |
| "recall": 0.9833333333333333, | |
| "f1-score": 0.9516129032258065, | |
| "support": 60.0 | |
| }, | |
| "VERB": { | |
| "precision": 0.84, | |
| "recall": 0.9, | |
| "f1-score": 0.8689655172413793, | |
| "support": 210.0 | |
| }, | |
| "X": { | |
| "precision": 0.0, | |
| "recall": 0.0, | |
| "f1-score": 0.0, | |
| "support": 0.0 | |
| }, | |
| "accuracy": 0.8929612661391088, | |
| "macro avg": { | |
| "precision": 0.7598283172178952, | |
| "recall": 0.767279052971072, | |
| "f1-score": 0.7618692914065028, | |
| "support": 2401.0 | |
| }, | |
| "weighted avg": { | |
| "precision": 0.8931804044150632, | |
| "recall": 0.8929612661391088, | |
| "f1-score": 0.8922390838062512, | |
| "support": 2401.0 | |
| } | |
| } |