camembert_ccnet_classification_tools_NEFTune_fr_lr1e-3_V2 – AI Model by AntoineD | AlphaNeural AI

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AntoineD/
camembert_ccnet_classification_tools_NEFTune_fr_lr1e-3_V2

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text-classification

generated_from_trainer

almanach/camembert-base-ccnet

autotrain_compatible

endpoints_compatible

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camembert_ccnet_classification_tools_NEFTune_fr_lr1e-3_V2

This model is a fine-tuned version of camembert/camembert-base-ccnet on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.0965
Accuracy: 0.1042
Learning Rate: 0.0008

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: 0.001
train_batch_size: 24
eval_batch_size: 192
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 60

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Rate
2.1119	1.0	15	2.1246	0.1042	0.0010
2.0909	2.0	30	2.1521	0.0938	0.0010
2.1043	3.0	45	2.0959	0.0938	0.0009
2.0866	4.0	60	2.1143	0.0938	0.0009
2.0746	5.0	75	2.1063	0.1354	0.0009
2.0753	6.0	90	2.1266	0.0938	0.0009
2.0793	7.0	105	2.1177	0.1146	0.0009
2.0844	8.0	120	2.0959	0.1354	0.0009
2.0855	9.0	135	2.1072	0.0938	0.0008
2.0805	10.0	150	2.1128	0.0938	0.0008
2.079	11.0	165	2.1027	0.1354	0.0008
2.0855	12.0	180	2.1164	0.0938	0.0008
2.0745	13.0	195	2.0965	0.1042	0.0008

Framework versions

Transformers 4.34.0
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.14.1