This model is a fine-tuned version of om-ashish-soni/pos-ner-tagging-v3 on the conll2003 dataset. It achieves the following results on the evaluation set:

Loss: 0.6642
Precision: 0.9243
Recall: 0.9264
F1: 0.9244
Accuracy: 0.9264

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: 32
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	0.98	54	0.6425	0.9254	0.9272	0.9250	0.9272
No log	1.99	109	0.6624	0.9239	0.9261	0.9240	0.9261
No log	2.99	164	0.6593	0.9245	0.9267	0.9245	0.9267
No log	3.99	219	0.6608	0.9251	0.9270	0.9250	0.9270
No log	4.99	274	0.6698	0.9246	0.9269	0.9245	0.9269
No log	6.0	329	0.6648	0.9246	0.9264	0.9244	0.9264
No log	7.0	384	0.6651	0.9244	0.9266	0.9245	0.9266
No log	7.87	432	0.6642	0.9243	0.9264	0.9244	0.9264

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-v4

pos-ner-tagging-v4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

om-ashish-soni/
pos-ner-tagging-v4