distilrubert_tiny-2nd-finetune-epru – AI Model by mmillet | AlphaNeural AI

You can deploy this model and start earning money today!

mmillet/
distilrubert_tiny-2nd-finetune-epru

like

0

text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

distilrubert_tiny-2nd-finetune-epru

This model is a fine-tuned version of mmillet/distilrubert-tiny-cased-conversational-v1_single_finetuned_on_cedr_augmented on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4467
Accuracy: 0.8712
F1: 0.8718
Precision: 0.8867
Recall: 0.8712

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: 0.0001
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.4947	1.0	12	0.4142	0.8773	0.8777	0.8907	0.8773
0.2614	2.0	24	0.3178	0.9018	0.9011	0.9069	0.9018
0.2079	3.0	36	0.3234	0.8773	0.8784	0.8850	0.8773
0.1545	4.0	48	0.3729	0.8834	0.8830	0.8946	0.8834
0.1028	5.0	60	0.2964	0.9018	0.9016	0.9073	0.9018
0.0986	6.0	72	0.2971	0.9141	0.9139	0.9152	0.9141
0.0561	7.0	84	0.3482	0.8957	0.8962	0.9023	0.8957
0.0336	8.0	96	0.3731	0.8957	0.8953	0.9014	0.8957
0.0364	9.0	108	0.4467	0.8712	0.8718	0.8867	0.8712

Framework versions

Transformers 4.20.0
Pytorch 1.11.0+cu113
Datasets 2.3.2
Tokenizers 0.12.1