multi_task_model_general_fine_tune – AI Model by ttqdunggg | AlphaNeural AI

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multi_task_model_general_fine_tune

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RonTon05/model_content_V2_test

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multi_task_model_general_fine_tune

This model is a fine-tuned version of RonTon05/model_content_V2_test on the None dataset. It achieves the following results on the evaluation set:

Acc Content: 0.9775
F1 Content: 0.9612
Acc Classification: 0.8299
F1 Classification: 0.7954
Loss: 0.6929

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Acc Content	F1 Content	Acc Classification	F1 Classification	Validation Loss
No log	1.0	276	0.9751	0.9569	0.8056	0.7523	0.7369
0.5614	2.0	552	0.9755	0.9582	0.8161	0.7741	0.6704
0.5614	3.0	828	0.9760	0.9582	0.8201	0.7709	0.6735
0.3769	4.0	1104	0.9766	0.9595	0.8263	0.7853	0.6859
0.3769	5.0	1380	0.9775	0.9612	0.8299	0.7954	0.6929

Framework versions

Transformers 4.57.1
Pytorch 2.6.0+cu124
Datasets 4.4.1
Tokenizers 0.22.1