frame_classification_bigbird – AI Model by AriyanH22 | AlphaNeural AI

You can deploy this model and start earning money today!

AriyanH22/
frame_classification_bigbird

like

0

text-classification

generated_from_trainer

google/bigbird-roberta-base

autotrain_compatible

endpoints_compatible

Views

No views yet

frame_classification_bigbird

This model is a fine-tuned version of google/bigbird-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.8803
Accuracy: 0.8991
F1: 0.9396
Precision: 0.9353
Recall: 0.9440

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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Accuracy	F1	Validation Loss	Precision	Recall
0.6673	1.0	1288	0.9270	0.9570	0.4955	0.9390	0.9757
0.5913	2.0	2576	0.9099	0.9477	0.6212	0.9178	0.9795
0.5858	3.0	3864	0.9270	0.9572	0.4327	0.9343	0.9813
0.5384	4.0	5152	0.9317	0.9599	0.4998	0.9377	0.9832
0.6131	5.0	6440	0.9255	0.9561	0.5642	0.9373	0.9757
0.5834	6.0	7728	0.9239	0.9553	0.6238	0.9340	0.9776
0.5023	7.0	9016	0.9208	0.9533	0.7194	0.9354	0.9720
0.5271	8.0	10304	0.9177	0.9516	0.7188	0.9320	0.9720
0.4755	9.0	11592	0.8618	0.9177	0.9514	0.9351	0.9683
0.4173	10.0	12880	0.8803	0.8991	0.9396	0.9353	0.9440

Framework versions

Transformers 4.38.2
Pytorch 2.2.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2