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metadata
base_model: bigcode/starencoder
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - accuracy
model-index:
  - name: stack-edu-classifier-javascript
    results: []

stack-edu-classifier-javascript

This model is a fine-tuned version of bigcode/starencoder on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3612
  • Precision: 0.5135
  • Recall: 0.3322
  • F1 Macro: 0.3711
  • Accuracy: 0.6277
  • F1 Binary Minimum3: 0.5704

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: 64
  • eval_batch_size: 256
  • seed: 0
  • distributed_type: multi-GPU
  • num_devices: 2
  • total_train_batch_size: 128
  • total_eval_batch_size: 512
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 200
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Macro Accuracy F1 Binary Minimum3
No log 0 0 5.6298 0.0010 0.1667 0.0020 0.0059 0
0.3853 1.4493 1000 0.3886 0.4945 0.3110 0.3354 0.6037 0.5761
0.3791 2.8986 2000 0.3729 0.5041 0.3090 0.3395 0.6208 0.5716
0.3722 4.3478 3000 0.3720 0.5261 0.3116 0.3440 0.6189 0.5673
0.3751 5.7971 4000 0.3704 0.5247 0.3204 0.3565 0.6199 0.5766
0.3651 7.2464 5000 0.3718 0.5113 0.3352 0.3678 0.6310 0.5161
0.3695 8.6957 6000 0.3649 0.5055 0.3253 0.3607 0.6249 0.5632
0.361 10.1449 7000 0.3647 0.5042 0.3236 0.3571 0.6354 0.5410
0.3666 11.5942 8000 0.3764 0.5290 0.3371 0.3752 0.6146 0.5941
0.3563 13.0435 9000 0.3617 0.5179 0.3356 0.3743 0.6303 0.5674
0.3735 14.4928 10000 0.3663 0.4998 0.3423 0.3760 0.6340 0.5320
0.349 15.9420 11000 0.3616 0.5063 0.3306 0.3681 0.6273 0.5696
0.3679 17.3913 12000 0.3632 0.5078 0.3396 0.3786 0.6252 0.5762
0.3622 18.8406 13000 0.3612 0.5135 0.3322 0.3711 0.6277 0.5704

Framework versions

  • Transformers 4.43.4
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1