metadata

tags:
  - generated_from_trainer
datasets:
  - DFKI-SLT/few-nerd
model-index:
  - name: span-marker-robert-base
    results: []
license: apache-2.0
language:
  - en

span-marker-robert-base

This model is a fine-tuned version of roberta-base on few-nerd dataset using SpanMarker an module for NER. It achieves the following results on the evaluation set:

Loss: 0.0214
Overall Precision: 0.7642
Overall Recall: 0.7947
Overall F1: 0.7791
Overall Accuracy: 0.9397

Training and evaluation data

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Overall Precision	Overall Recall	Overall F1	Overall Accuracy
0.0214	0.08	100	0.0219	0.7641	0.7679	0.7660	0.9330
0.0199	0.16	200	0.0243	0.7442	0.7679	0.7559	0.9348
0.0179	0.24	300	0.0212	0.7730	0.7580	0.7654	0.9361
0.0188	0.33	400	0.0225	0.7616	0.7710	0.7662	0.9343
0.0149	0.41	500	0.0240	0.7537	0.7783	0.7658	0.9375
0.015	0.49	600	0.0230	0.7540	0.7829	0.7682	0.9362
0.0137	0.57	700	0.0232	0.7746	0.7538	0.7640	0.9319
0.0123	0.65	800	0.0218	0.7651	0.7879	0.7763	0.9393
0.0103	0.73	900	0.0223	0.7688	0.7964	0.7824	0.9397
0.0108	0.82	1000	0.0209	0.7763	0.7816	0.7789	0.9397
0.0116	0.9	1100	0.0213	0.7743	0.7879	0.7811	0.9398
0.0119	0.98	1200	0.0214	0.7653	0.7947	0.7797	0.9400

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3