FRA_party_tweets_climate – AI Model by mljn | AlphaNeural AI

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mljn/
FRA_party_tweets_climate

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text-classification

generated_from_trainer

almanach/camembert-base

autotrain_compatible

endpoints_compatible

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FRA_party_tweets_climate

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

Loss: 0.0826
Accuracy: 0.9857
F1 Macro: 0.9853
Accuracy Balanced: 0.9847
F1 Micro: 0.9857
Precision Macro: 0.9858
Recall Macro: 0.9847
Precision Micro: 0.9857
Recall Micro: 0.9857

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: 8
eval_batch_size: 80
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.06
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro	Accuracy Balanced	F1 Micro	Precision Macro	Recall Macro	Precision Micro	Recall Micro
0.2428	1.0	628	0.0792	0.9841	0.9836	0.9831	0.9841	0.9842	0.9831	0.9841	0.9841
0.058	2.0	1256	0.0925	0.9809	0.9804	0.9804	0.9809	0.9804	0.9804	0.9809	0.9809
0.0429	3.0	1884	0.0785	0.9857	0.9852	0.9846	0.9857	0.9859	0.9846	0.9857	0.9857
0.024	4.0	2512	0.0829	0.9857	0.9853	0.9847	0.9857	0.9858	0.9847	0.9857	0.9857
0.0202	5.0	3140	0.0826	0.9857	0.9853	0.9847	0.9857	0.9858	0.9847	0.9857	0.9857

Framework versions

Transformers 4.35.2
Pytorch 2.1.1+cu121
Datasets 2.15.0
Tokenizers 0.15.0