gbert-large-AmDi.tiny-synset-classifier – AI Model by kugler | AlphaNeural AI

You can deploy this model and start earning money today!

kugler/
gbert-large-AmDi.tiny-synset-classifier

like

0

text-classification

generated_from_trainer

deepset/gbert-large

autotrain_compatible

endpoints_compatible

Views

No views yet

gbert_synset_classifier_amdi_tiny

This model is a fine-tuned version of deepset/gbert-large on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6469
Accuracy: 0.8376
F1: 0.8366
Precision: 0.8446
Recall: 0.8376
F1 Macro: 0.8202
Precision Macro: 0.7900
Recall Macro: 0.8625
F1 Micro: 0.8376
Precision Micro: 0.8376
Recall Micro: 0.8376

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
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	F1 Macro	Precision Macro	Recall Macro	F1 Micro	Precision Micro	Recall Micro
2.7014	0.8584	100	1.1834	0.6919	0.6499	0.6573	0.6919	0.4964	0.5670	0.4997	0.6919	0.6919	0.6919
0.7696	1.7167	200	0.5970	0.8241	0.8188	0.8227	0.8241	0.7784	0.7603	0.8062	0.8241	0.8241	0.8241
0.4739	2.5751	300	0.5408	0.8321	0.8290	0.8381	0.8321	0.8082	0.7815	0.8508	0.8321	0.8321	0.8321
0.3743	3.4335	400	0.5343	0.8426	0.8385	0.8480	0.8426	0.8269	0.8046	0.8598	0.8426	0.8426	0.8426
0.2931	4.2918	500	0.5188	0.8469	0.8465	0.8516	0.8469	0.8312	0.8133	0.8552	0.8469	0.8469	0.8469
0.2175	5.1502	600	0.5697	0.8426	0.8419	0.8506	0.8426	0.8295	0.8093	0.8572	0.8426	0.8426	0.8426
0.1689	6.0086	700	0.5781	0.8426	0.8421	0.8470	0.8426	0.8322	0.8164	0.8540	0.8426	0.8426	0.8426
0.1174	6.8670	800	0.6469	0.8376	0.8366	0.8446	0.8376	0.8202	0.7900	0.8625	0.8376	0.8376	0.8376

Framework versions

Transformers 4.45.2
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.20.3