semeval_taskA_model – AI Model by sohailtsm | AlphaNeural AI

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sohailtsm/
semeval_taskA_model

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text-classification

generated_from_trainer

microsoft/codebert-base

endpoints_compatible

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semeval_taskA_model

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

Loss: 0.3545
Accuracy: 0.9136
F1: 0.9132
Precision: 0.9202
Recall: 0.9136

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: 1e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5
mixed_precision_training: Native AMP
label_smoothing_factor: 0.1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.5408	0.2541	200	0.5332	0.7773	0.7712	0.8102	0.7773
0.391	0.5083	400	0.5409	0.8140	0.8085	0.8545	0.8140
0.3775	0.7624	600	0.3763	0.8934	0.8929	0.9023	0.8934
0.33	1.0165	800	0.3793	0.8976	0.8970	0.9064	0.8976
0.3171	1.2706	1000	0.3558	0.9070	0.9066	0.9134	0.9070
0.3062	1.5248	1200	0.3388	0.9189	0.9188	0.9226	0.9189
0.2924	1.7789	1400	0.3567	0.9077	0.9073	0.9157	0.9077
0.2864	2.0330	1600	0.3545	0.9136	0.9132	0.9202	0.9136

Framework versions

Transformers 4.45.0
Pytorch 2.10.0+cu128
Datasets 4.8.3
Tokenizers 0.20.3