This model is a fine-tuned version of om-ashish-soni/pos-ner-tagging-v2 on the conll2003 dataset. It achieves the following results on the evaluation set:

Loss: 0.6356
Precision: 0.9339
Recall: 0.9374
F1: 0.9357
Accuracy: 0.9273

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	439	0.6415	0.9341	0.9367	0.9354	0.9265
0.0078	2.0	878	0.6372	0.9327	0.9363	0.9345	0.9259
0.006	3.0	1317	0.6283	0.9338	0.9373	0.9356	0.9274
0.0036	4.0	1756	0.6356	0.9339	0.9374	0.9357	0.9273

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3

om-ashish-soni/pos-ner-tagging-v3

pos-ner-tagging-v3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

om-ashish-soni/
pos-ner-tagging-v3