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scenario-KD-PR-MSV-D2_data-cl-cardiff_cl_only55

PyTorch
deberta-v2
Generated from Trainer
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metadata
license: mit
base_model: haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: scenario-KD-PR-MSV-D2_data-cl-cardiff_cl_only55
    results: []

scenario-KD-PR-MSV-D2_data-cl-cardiff_cl_only55

This model is a fine-tuned version of haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3677
  • Accuracy: 0.4468
  • F1: 0.4461

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: 32
  • eval_batch_size: 32
  • seed: 55
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
No log 1.09 250 1.2834 0.4591 0.4503
1.2011 2.17 500 1.3504 0.4483 0.4403
1.2011 3.26 750 1.3205 0.4468 0.4415
1.0583 4.35 1000 1.3622 0.4406 0.4355
1.0583 5.43 1250 1.3754 0.4375 0.4333
0.9917 6.52 1500 1.3816 0.4398 0.4380
0.9917 7.61 1750 1.3783 0.4475 0.4434
0.9569 8.7 2000 1.3621 0.4529 0.4497
0.9569 9.78 2250 1.3658 0.4460 0.4450
0.939 10.87 2500 1.3567 0.4630 0.4616
0.939 11.96 2750 1.3631 0.4676 0.4675
0.9262 13.04 3000 1.3922 0.4421 0.4304
0.9262 14.13 3250 1.3950 0.4275 0.4135
0.9176 15.22 3500 1.3653 0.4660 0.4658
0.9176 16.3 3750 1.3690 0.4498 0.4449
0.9114 17.39 4000 1.3964 0.4398 0.4336
0.9114 18.48 4250 1.3738 0.4614 0.4600
0.9058 19.57 4500 1.3574 0.4730 0.4728
0.9058 20.65 4750 1.3716 0.4606 0.4577
0.9018 21.74 5000 1.3684 0.4583 0.4578
0.9018 22.83 5250 1.3791 0.4568 0.4534
0.8988 23.91 5500 1.3708 0.4560 0.4549
0.8988 25.0 5750 1.3438 0.4730 0.4728
0.8963 26.09 6000 1.3544 0.4622 0.4615
0.8963 27.17 6250 1.3508 0.4622 0.4590
0.8937 28.26 6500 1.3531 0.4637 0.4633
0.8937 29.35 6750 1.3677 0.4468 0.4461

Framework versions

  • Transformers 4.33.3
  • Pytorch 2.1.1+cu121
  • Datasets 2.14.5
  • Tokenizers 0.13.3