checkpoints_27_9_microsoft_deberta_21_9

This model is a fine-tuned version of VuongQuoc/checkpoints_26_9_microsoft_deberta_21_9 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.6632
• Map@3: 0.8608
• Accuracy: 0.775
• MAX_INPUT = 256

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: 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: 0.2
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Map@3	Accuracy
0.6308	0.05	100	0.6775	0.8842	0.815
0.3472	0.11	200	0.7255	0.8767	0.805
0.2267	0.16	300	0.7786	0.8608	0.785
0.143	0.21	400	0.8580	0.8333	0.735
0.0723	0.27	500	0.9517	0.8358	0.735
0.3952	0.32	600	0.6632	0.8608	0.775

Framework versions

• Transformers 4.32.1
• Pytorch 2.0.0
• Datasets 2.9.0
• Tokenizers 0.13.3