augmented_model_final – AI Model by LeonardoFettucciari | AlphaNeural AI

You can deploy this model and start earning money today!

LeonardoFettucciari/
augmented_model_final

like

0

text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

Views

No views yet

augmented_model_final

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

Loss: 1.1929
Accuracy: 0.5697
F1: 0.5699
Precision: 0.5731
Recall: 0.5691

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: 1e-05
train_batch_size: 32
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.9553	0.2088	500	0.7998	0.6477	0.6332	0.6457	0.6376
0.6974	0.4175	1000	0.7414	0.6936	0.6792	0.6934	0.6830
0.6307	0.6263	1500	0.7166	0.7190	0.7076	0.7143	0.7097
0.5916	0.8351	2000	0.7050	0.7212	0.7126	0.7173	0.7136
0.5517	1.0438	2500	0.7218	0.7229	0.7148	0.7209	0.7157
0.4939	1.2526	3000	0.7427	0.7316	0.7220	0.7309	0.7232
0.4823	1.4614	3500	0.7474	0.7233	0.7143	0.7181	0.7154
0.4771	1.6701	4000	0.7451	0.7295	0.7198	0.7252	0.7210
0.4649	1.8789	4500	0.7484	0.7316	0.7222	0.7269	0.7234

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1