CoolFace
Modelpublic

OnePoint16/distilbert-medical-question_answer

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
2likes23downloads
Model Card

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distilbert-medical-question_answer

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 5.6100

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
  • —trainbatchsize: 16
  • —evalbatchsize: 16
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 100

Training results

Training LossEpochStepValidation Loss
No log1.0214.2930
No log2.0423.3634
No log3.0633.2834
No log4.0843.2596
No log5.01053.2594
No log6.01263.2574
No log7.01473.2845
No log8.01683.2187
No log9.01893.3233
No log10.02103.3231
No log11.02313.3505
No log12.02523.5721
No log13.02733.5463
No log14.02943.5413
No log15.03153.6203
No log16.03363.6025
No log17.03573.6301
No log18.03783.8150
No log19.03994.0084
No log20.04203.9528
No log21.04414.0350
No log22.04623.9436
No log23.04834.0115
1.750824.05044.0571
1.750825.05254.0290
1.750826.05464.0609
1.750827.05674.2875
1.750828.05884.0578
1.750829.06094.1743
1.750830.06304.1155
1.750831.06514.2136
1.750832.06724.3880
1.750833.06934.4454
1.750834.07144.3621
1.750835.07354.1829
1.750836.07564.2985
1.750837.07774.5783
1.750838.07984.4504
1.750839.08194.6955
1.750840.08404.5165
1.750841.08614.3018
1.750842.08824.5299
1.750843.09034.6147
1.750844.09244.4756
1.750845.09454.6782
1.750846.09664.6168
1.750847.09874.7553
0.231848.010084.8580
0.231849.010294.8970
0.231850.010504.8502
0.231851.010714.7219
0.231852.010924.9355
0.231853.011135.0003
0.231854.011345.1603
0.231855.011555.0398
0.231856.011765.1349
0.231857.011975.1403
0.231858.012185.0170
0.231859.012395.0553
0.231860.012605.2331
0.231861.012815.0543
0.231862.013025.1769
0.231863.013235.4024
0.231864.013445.2960
0.231865.013655.2071
0.231866.013865.1635
0.231867.014075.2613
0.231868.014285.3370
0.231869.014495.3725
0.231870.014705.2739
0.231871.014915.2887
0.036372.015125.4713
0.036373.015335.4102
0.036374.015545.3190
0.036375.015755.3406
0.036376.015965.4775
0.036377.016175.4636
0.036378.016385.4894
0.036379.016595.5111
0.036380.016805.5769
0.036381.017015.5069
0.036382.017225.5296
0.036383.017435.5471
0.036384.017645.5630
0.036385.017855.5563
0.036386.018065.5700
0.036387.018275.6082
0.036388.018485.5808
0.036389.018695.5351
0.036390.018905.4856
0.036391.019115.5007
0.036392.019325.5076
0.036393.019535.5377
0.036394.019745.5612
0.036395.019955.5754
0.006796.020165.5861
0.006797.020375.5973
0.006798.020585.6035
0.006799.020795.6073
0.0067100.021005.6100

Framework versions

  • —Transformers 4.31.0
  • —Pytorch 2.0.1+cu118
  • —Datasets 2.14.4
  • —Tokenizers 0.13.3