relatives_psr_seq-cbert_finetuned – AI Model by djamina | AlphaNeural AI

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djamina/
relatives_psr_seq-cbert_finetuned

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token-classification

generated_from_trainer

djamina/relatives_psr

almanach/camembert-large

autotrain_compatible

endpoints_compatible

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relatives_psr_seq-cbert_finetuned

This model is a fine-tuned version of camembert/camembert-large on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.7099
Precision: 0.6914
Recall: 0.2252
F1: 0.2193
Accuracy: 0.7578

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: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	49	0.8241	0.9512	0.2	0.1722	0.7560
No log	2.0	98	0.8026	0.8243	0.2100	0.1933	0.7555
No log	3.0	147	0.7535	0.8077	0.2045	0.1823	0.7563
No log	4.0	196	0.7228	0.8227	0.2220	0.2109	0.7586
No log	5.0	245	0.7099	0.6914	0.2252	0.2193	0.7578

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1