all_abstracts_multi-qa-MiniLM-L6-cos-v1

This model is a fine-tuned version of sentence-transformers/multi-qa-MiniLM-L6-cos-v1 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 2.5678
  • Accuracy: 0.4621
  • Precision: 0.4621
  • Recall: 0.4621
  • F1: 0.4621

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
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
2.466 1.0 660 2.0039 0.3212 0.3212 0.3212 0.3212
2.0309 2.0 1320 1.8715 0.4061 0.4061 0.4061 0.4061
1.9092 3.0 1980 1.7737 0.4288 0.4288 0.4288 0.4288
1.6374 4.0 2640 1.7987 0.4606 0.4606 0.4606 0.4606
1.5152 5.0 3300 1.8548 0.4606 0.4606 0.4606 0.4606
1.4285 6.0 3960 1.8773 0.4712 0.4712 0.4712 0.4712
1.1618 7.0 4620 1.9726 0.4545 0.4545 0.4545 0.4545
1.104 8.0 5280 2.0739 0.4652 0.4652 0.4652 0.4652
1.025 9.0 5940 2.2104 0.4545 0.4545 0.4545 0.4545
0.9051 10.0 6600 2.2647 0.4545 0.4545 0.4545 0.4545
0.8191 11.0 7260 2.3455 0.4576 0.4576 0.4576 0.4576
0.8319 12.0 7920 2.4673 0.4652 0.4652 0.4652 0.4652
0.7634 13.0 8580 2.4986 0.4621 0.4621 0.4621 0.4621
0.7199 14.0 9240 2.5761 0.4636 0.4636 0.4636 0.4636
0.737 15.0 9900 2.5678 0.4621 0.4621 0.4621 0.4621

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.2.1+cu118
  • Datasets 2.14.7
  • Tokenizers 0.15.2
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