movieHunt4-ner

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0005
• Precision: 1.0
• Recall: 1.0
• F1: 1.0
• Accuracy: 1.0

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	48	0.0284	0.9959	0.9959	0.9959	0.9974
No log	2.0	96	0.0060	1.0	1.0	1.0	1.0
No log	3.0	144	0.0034	1.0	1.0	1.0	1.0
No log	4.0	192	0.0025	1.0	1.0	1.0	1.0
No log	5.0	240	0.0020	1.0	1.0	1.0	1.0
No log	6.0	288	0.0016	1.0	1.0	1.0	1.0
No log	7.0	336	0.0014	1.0	1.0	1.0	1.0
No log	8.0	384	0.0012	1.0	1.0	1.0	1.0
No log	9.0	432	0.0011	1.0	1.0	1.0	1.0
No log	10.0	480	0.0010	1.0	1.0	1.0	1.0
0.0168	11.0	528	0.0009	1.0	1.0	1.0	1.0
0.0168	12.0	576	0.0009	1.0	1.0	1.0	1.0
0.0168	13.0	624	0.0008	1.0	1.0	1.0	1.0
0.0168	14.0	672	0.0008	1.0	1.0	1.0	1.0
0.0168	15.0	720	0.0008	1.0	1.0	1.0	1.0
0.0168	16.0	768	0.0007	1.0	1.0	1.0	1.0
0.0168	17.0	816	0.0007	1.0	1.0	1.0	1.0
0.0168	18.0	864	0.0007	1.0	1.0	1.0	1.0
0.0168	19.0	912	0.0006	1.0	1.0	1.0	1.0
0.0168	20.0	960	0.0006	1.0	1.0	1.0	1.0
0.0014	21.0	1008	0.0006	1.0	1.0	1.0	1.0
0.0014	22.0	1056	0.0006	1.0	1.0	1.0	1.0
0.0014	23.0	1104	0.0006	1.0	1.0	1.0	1.0
0.0014	24.0	1152	0.0006	1.0	1.0	1.0	1.0
0.0014	25.0	1200	0.0005	1.0	1.0	1.0	1.0
0.0014	26.0	1248	0.0005	1.0	1.0	1.0	1.0
0.0014	27.0	1296	0.0005	1.0	1.0	1.0	1.0
0.0014	28.0	1344	0.0005	1.0	1.0	1.0	1.0
0.0014	29.0	1392	0.0005	1.0	1.0	1.0	1.0
0.0014	30.0	1440	0.0005	1.0	1.0	1.0	1.0

Framework versions

• Transformers 4.21.0
• Pytorch 1.12.0+cu113
• Datasets 2.4.0
• Tokenizers 0.12.1