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stack-edu-classifier-rust

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

stack-edu-classifier-rust

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

  • Loss: 0.4309
  • Precision: 0.4200
  • Recall: 0.3245
  • F1 Macro: 0.3364
  • Accuracy: 0.5715
  • F1 Binary Minimum3: 0.6938

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 6.3938 0.0009 0.1667 0.0018 0.0054 0
0.4784 1.4535 1000 0.4524 0.4359 0.3052 0.3115 0.5596 0.6790
0.4553 2.9070 2000 0.4622 0.4179 0.3081 0.3193 0.5299 0.7012
0.4397 4.3605 3000 0.4428 0.4256 0.3126 0.3225 0.5646 0.6890
0.4463 5.8140 4000 0.4417 0.4252 0.3155 0.3242 0.5667 0.6850
0.4305 7.2674 5000 0.4419 0.4416 0.3232 0.3397 0.5488 0.7001
0.4499 8.7209 6000 0.4361 0.4250 0.3185 0.3282 0.5682 0.6878
0.4339 10.1744 7000 0.4351 0.4452 0.3258 0.3384 0.5711 0.6884
0.449 11.6279 8000 0.4386 0.4217 0.3180 0.3291 0.5718 0.6782
0.425 13.0814 9000 0.4360 0.4224 0.3213 0.3323 0.5737 0.6828
0.4434 14.5349 10000 0.4328 0.4376 0.3280 0.3436 0.5626 0.6957
0.4396 15.9884 11000 0.4347 0.4170 0.3243 0.3384 0.5576 0.6994
0.4207 17.4419 12000 0.4326 0.4181 0.3233 0.3365 0.5606 0.6996
0.4334 18.8953 13000 0.4309 0.4200 0.3245 0.3364 0.5715 0.6938

Framework versions

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