codegen-350M-mono-measurement_pred-diamonds-seed0 – AI Model by oliverdk | AlphaNeural AI

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oliverdk/
codegen-350M-mono-measurement_pred-diamonds-seed0

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Salesforce/codegen-350M-mono

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codegen-350M-mono-measurement_pred-diamonds-seed0

This model is a fine-tuned version of Salesforce/codegen-350M-mono on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3882
Accuracy: 0.9138
Accuracy Sensor 0: 0.9051
Auroc Sensor 0: 0.9644
Accuracy Sensor 1: 0.9165
Auroc Sensor 1: 0.9454
Accuracy Sensor 2: 0.9324
Auroc Sensor 2: 0.9773
Accuracy Aggregated: 0.9010
Auroc Aggregated: 0.9670

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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 64
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Accuracy Sensor 0	Auroc Sensor 0	Accuracy Sensor 1	Auroc Sensor 1	Accuracy Sensor 2	Auroc Sensor 2	Accuracy Aggregated	Auroc Aggregated
0.2891	0.9997	781	0.3732	0.8385	0.8367	0.9076	0.8089	0.9026	0.8669	0.9409	0.8414	0.9123
0.179	1.9994	1562	0.3287	0.8639	0.8532	0.9392	0.8835	0.9339	0.8852	0.9648	0.8338	0.9430
0.1181	2.9990	2343	0.2500	0.9084	0.8967	0.9587	0.9138	0.9382	0.9327	0.9744	0.8906	0.9623
0.0614	4.0	3125	0.3212	0.9095	0.8961	0.9636	0.9145	0.9457	0.9238	0.9774	0.9036	0.9662
0.0267	4.9984	3905	0.3882	0.9138	0.9051	0.9644	0.9165	0.9454	0.9324	0.9773	0.9010	0.9670

Framework versions

Transformers 4.41.0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1