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python-edu-scorer

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metadata
license: apache-2.0
base_model: Snowflake/snowflake-arctic-embed-m
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - accuracy
model-index:
  - name: stack-edu-scorer
    results: []

stack-edu-scorer

This model is a fine-tuned version of Snowflake/snowflake-arctic-embed-m on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3426
  • Precision: 0.5188
  • Recall: 0.3971
  • F1 Macro: 0.4258
  • Accuracy: 0.6350

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: 0.0003
  • train_batch_size: 256
  • eval_batch_size: 128
  • seed: 0
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Macro Accuracy
0.3973 0.5787 1000 0.3904 0.4701 0.3433 0.3701 0.5885
0.3848 1.1574 2000 0.3803 0.5107 0.3574 0.3863 0.5974
0.3667 1.7361 3000 0.3715 0.6471 0.4478 0.4879 0.6103
0.3727 2.3148 4000 0.3655 0.6140 0.4375 0.4715 0.6121
0.3639 2.8935 5000 0.3617 0.6234 0.4519 0.4879 0.6176
0.3684 3.4722 6000 0.3626 0.6424 0.4632 0.5020 0.6211
0.3557 4.0509 7000 0.3589 0.5519 0.3739 0.4032 0.6175
0.3513 4.6296 8000 0.3650 0.6328 0.4671 0.5010 0.6241
0.3505 5.2083 9000 0.3535 0.5320 0.3850 0.4129 0.6259
0.3549 5.7870 10000 0.3526 0.6358 0.4588 0.4949 0.6248
0.3465 6.3657 11000 0.3580 0.5204 0.3712 0.3970 0.6166
0.3468 6.9444 12000 0.3498 0.5266 0.3936 0.4235 0.6293
0.3463 7.5231 13000 0.3497 0.6837 0.4661 0.4999 0.6300
0.3404 8.1019 14000 0.3557 0.6169 0.4940 0.5285 0.6307
0.3381 8.6806 15000 0.3493 0.5124 0.3871 0.4135 0.6290
0.342 9.2593 16000 0.3482 0.5265 0.3959 0.4247 0.6337
0.3397 9.8380 17000 0.3477 0.5210 0.3919 0.4191 0.6325
0.3407 10.4167 18000 0.3465 0.5380 0.3895 0.4202 0.6297
0.3303 10.9954 19000 0.3471 0.5273 0.3952 0.4234 0.6355
0.3296 11.5741 20000 0.3447 0.5428 0.3891 0.4173 0.6313
0.3299 12.1528 21000 0.3451 0.5173 0.3964 0.4248 0.6347
0.3316 12.7315 22000 0.3448 0.6321 0.4809 0.5167 0.6350
0.3289 13.3102 23000 0.3446 0.5100 0.3969 0.4242 0.6358
0.3278 13.8889 24000 0.3445 0.5451 0.3918 0.4223 0.6327
0.3249 14.4676 25000 0.3440 0.5282 0.3915 0.4194 0.6343
0.328 15.0463 26000 0.3438 0.5670 0.3880 0.4183 0.6316
0.3263 15.625 27000 0.3448 0.6290 0.4828 0.5191 0.6363
0.3243 16.2037 28000 0.3437 0.5534 0.3950 0.4252 0.6356
0.3265 16.7824 29000 0.3435 0.5432 0.3926 0.4217 0.6328
0.3193 17.3611 30000 0.3432 0.5231 0.3962 0.4238 0.6348
0.3261 17.9398 31000 0.3433 0.5517 0.3933 0.4235 0.6326
0.317 18.5185 32000 0.3431 0.5527 0.3929 0.4220 0.6334
0.3222 19.0972 33000 0.3429 0.5132 0.3976 0.4259 0.6357
0.3223 19.6759 34000 0.3426 0.5188 0.3971 0.4258 0.6350

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.2.0+cu121
  • Datasets 2.17.1
  • Tokenizers 0.19.1