distilbert-base-uncased-finetuned-tweet_pemilu2024 – AI Model by tunarebus | AlphaNeural AI

You can deploy this model and start earning money today!

tunarebus/
distilbert-base-uncased-finetuned-tweet_pemilu2024

like

0

generated_from_keras_callback

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

Views

No views yet

tunarebus/distilbert-base-uncased-finetuned-tweet_pemilu2024

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 2.5045
Validation Loss: 2.4250
Epoch: 24

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:

optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -931, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
training_precision: mixed_float16

Training results

Train Loss	Validation Loss	Epoch
4.9932	4.6882	0
4.6678	4.3954	1
4.4076	4.1306	2
4.1610	3.8876	3
3.9036	3.6392	4
3.6549	3.4398	5
3.4439	3.2595	6
3.3055	3.0760	7
3.1307	2.8918	8
2.9749	2.8005	9
2.8441	2.7331	10
2.7790	2.6070	11
2.6932	2.5804	12
2.6181	2.4717	13
2.5241	2.4091	14
2.4900	2.4074	15
2.5065	2.4340	16
2.4976	2.4425	17
2.4894	2.4307	18
2.5294	2.4356	19
2.4649	2.4002	20
2.5011	2.4172	21
2.5083	2.4533	22
2.4822	2.4224	23
2.5045	2.4250	24

Framework versions

Transformers 4.35.2
TensorFlow 2.15.0
Datasets 2.15.0
Tokenizers 0.15.0