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enoriega/
rule_learning_1mm_many_negatives_spanpred_margin_avg

Name: rule_learning_1mm_many_negatives_spanpred_margin_avg
Availability: InStock

generated_from_trainer

enoriega/odinsynth_dataset

endpoints_compatible

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rule_learning_1mm_many_negatives_spanpred_margin_avg

This model is a fine-tuned version of enoriega/rule_softmatching on the enoriega/odinsynth_dataset dataset. It achieves the following results on the evaluation set:

Loss: 0.2421
Margin Accuracy: 0.8897

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: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 2000
total_train_batch_size: 8000
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Margin Accuracy
0.3867	0.16	20	0.4023	0.8187
0.3506	0.32	40	0.3381	0.8523
0.3195	0.48	60	0.3096	0.8613
0.3052	0.64	80	0.2957	0.8640
0.2859	0.8	100	0.2922	0.8679
0.297	0.96	120	0.2871	0.8688
0.2717	1.12	140	0.2761	0.8732
0.2671	1.28	160	0.2751	0.8743
0.2677	1.44	180	0.2678	0.8757
0.2693	1.6	200	0.2627	0.8771
0.2675	1.76	220	0.2573	0.8813
0.2732	1.92	240	0.2546	0.8858
0.246	2.08	260	0.2478	0.8869
0.2355	2.24	280	0.2463	0.8871
0.2528	2.4	300	0.2449	0.8886
0.2512	2.56	320	0.2443	0.8892
0.2527	2.72	340	0.2441	0.8893
0.2346	2.88	360	0.2424	0.8895

Framework versions

Transformers 4.19.2
Pytorch 1.11.0
Datasets 2.2.1
Tokenizers 0.12.1

enoriega/rule_learning_1mm_many_negatives_spanpred_margin_avg

rule_learning_1mm_many_negatives_spanpred_margin_avg

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

enoriega/
rule_learning_1mm_many_negatives_spanpred_margin_avg