# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("Bachi06/roberta-base-ner-updated")
model = AutoModelForTokenClassification.from_pretrained("Bachi06/roberta-base-ner-updated")Quick Links
roberta-base-ner-updated
This model is a fine-tuned version of Bachi06/roberta-base-ner-demo on the None dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
- Downloads last month
- 1
Model tree for Bachi06/roberta-base-ner-updated
Base model
bayartsogt/mongolian-roberta-base Finetuned
Bachi06/roberta-base-ner-demo
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Bachi06/roberta-base-ner-updated")