1_microsoft_deberta_V1.1 – AI Model by VuongQuoc | AlphaNeural AI

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1_microsoft_deberta_V1.1

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1_microsoft_deberta_V1.1

This model is a fine-tuned version of microsoft/deberta-v3-large on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7138
Map@3: 0.8492
Accuracy: 0.775

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: 2
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Map@3	Accuracy
1.6141	0.03	50	1.6087	0.6242	0.51
1.336	0.05	100	1.1398	0.7550	0.645
0.9441	0.08	150	0.8809	0.8150	0.7
0.9279	0.11	200	0.7528	0.8383	0.73
0.8639	0.13	250	0.7259	0.8525	0.76
0.8255	0.16	300	0.7363	0.8592	0.785
0.8411	0.19	350	0.7052	0.8483	0.76
0.856	0.21	400	0.7097	0.8408	0.745
0.7753	0.24	450	0.6860	0.8575	0.775
0.7941	0.27	500	0.7146	0.8525	0.765
0.8062	0.29	550	0.7138	0.8492	0.775

Framework versions

Transformers 4.32.1
Pytorch 2.0.0
Datasets 2.9.0
Tokenizers 0.13.3