Hugging Face's logo

YCheetax
/
esm2_t12_35M_UR50D-finetuned-localization

Text Classification
Transformers
PyTorch
TensorBoard
esm
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
esm2_t12_35M_UR50D-finetuned-localization / README.md
YCheetax's picture
YCheetax
Model save
9787c82 verified
preview code
|
raw
history blame
No virus
7.45 kB
metadata
license: mit
base_model: facebook/esm2_t12_35M_UR50D
tags:
  - generated_from_trainer
metrics:
  - f1
model-index:
  - name: esm2_t12_35M_UR50D-finetuned-localization
    results: []

esm2_t12_35M_UR50D-finetuned-localization

This model is a fine-tuned version of facebook/esm2_t12_35M_UR50D on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 4.3200
  • F1: 0.0208

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
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 3
  • total_train_batch_size: 24
  • total_eval_batch_size: 24
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 100

Training results

Training Loss Epoch Step Validation Loss F1
No log 1.0 5 9.0954 0.0
No log 2.0 10 9.0396 0.0
No log 3.0 15 8.9842 0.0180
No log 4.0 20 8.9289 0.0208
No log 5.0 25 8.8736 0.0208
No log 6.0 30 8.8179 0.0208
No log 7.0 35 8.7617 0.0208
No log 8.0 40 8.7048 0.0208
No log 9.0 45 8.6472 0.0208
No log 10.0 50 8.5888 0.0208
No log 11.0 55 8.5294 0.0208
No log 12.0 60 8.4687 0.0208
No log 13.0 65 8.4071 0.0208
No log 14.0 70 8.3442 0.0208
No log 15.0 75 8.2803 0.0208
No log 16.0 80 8.2152 0.0208
No log 17.0 85 8.1491 0.0208
No log 18.0 90 8.0819 0.0208
No log 19.0 95 8.0136 0.0208
No log 20.0 100 7.9443 0.0208
No log 21.0 105 7.8741 0.0208
No log 22.0 110 7.8029 0.0208
No log 23.0 115 7.7308 0.0208
No log 24.0 120 7.6576 0.0208
No log 25.0 125 7.5834 0.0208
No log 26.0 130 7.5083 0.0208
No log 27.0 135 7.4330 0.0208
No log 28.0 140 7.3573 0.0208
No log 29.0 145 7.2820 0.0208
No log 30.0 150 7.2068 0.0208
No log 31.0 155 7.1315 0.0208
No log 32.0 160 7.0560 0.0208
No log 33.0 165 6.9807 0.0208
No log 34.0 170 6.9055 0.0208
No log 35.0 175 6.8307 0.0208
No log 36.0 180 6.7565 0.0208
No log 37.0 185 6.6831 0.0208
No log 38.0 190 6.6100 0.0208
No log 39.0 195 6.5380 0.0208
No log 40.0 200 6.4667 0.0208
No log 41.0 205 6.3962 0.0208
No log 42.0 210 6.3268 0.0208
No log 43.0 215 6.2585 0.0208
No log 44.0 220 6.1912 0.0208
No log 45.0 225 6.1249 0.0208
No log 46.0 230 6.0597 0.0208
No log 47.0 235 5.9954 0.0208
No log 48.0 240 5.9325 0.0208
No log 49.0 245 5.8706 0.0208
No log 50.0 250 5.8102 0.0208
No log 51.0 255 5.7507 0.0208
No log 52.0 260 5.6925 0.0208
No log 53.0 265 5.6356 0.0208
No log 54.0 270 5.5795 0.0208
No log 55.0 275 5.5251 0.0208
No log 56.0 280 5.4714 0.0208
No log 57.0 285 5.4190 0.0208
No log 58.0 290 5.3679 0.0208
No log 59.0 295 5.3180 0.0208
No log 60.0 300 5.2690 0.0208
No log 61.0 305 5.2213 0.0208
No log 62.0 310 5.1749 0.0208
No log 63.0 315 5.1301 0.0208
No log 64.0 320 5.0863 0.0208
No log 65.0 325 5.0441 0.0208
No log 66.0 330 5.0031 0.0208
No log 67.0 335 4.9627 0.0208
No log 68.0 340 4.9235 0.0208
No log 69.0 345 4.8856 0.0208
No log 70.0 350 4.8490 0.0208
No log 71.0 355 4.8138 0.0208
No log 72.0 360 4.7801 0.0208
No log 73.0 365 4.7474 0.0208
No log 74.0 370 4.7158 0.0208
No log 75.0 375 4.6857 0.0208
No log 76.0 380 4.6567 0.0208
No log 77.0 385 4.6289 0.0208
No log 78.0 390 4.6021 0.0208
No log 79.0 395 4.5767 0.0208
No log 80.0 400 4.5527 0.0208
No log 81.0 405 4.5299 0.0208
No log 82.0 410 4.5085 0.0208
No log 83.0 415 4.4883 0.0208
No log 84.0 420 4.4691 0.0208
No log 85.0 425 4.4511 0.0208
No log 86.0 430 4.4344 0.0208
No log 87.0 435 4.4188 0.0208
No log 88.0 440 4.4043 0.0208
No log 89.0 445 4.3909 0.0208
No log 90.0 450 4.3786 0.0208
No log 91.0 455 4.3674 0.0208
No log 92.0 460 4.3574 0.0208
No log 93.0 465 4.3488 0.0208
No log 94.0 470 4.3412 0.0208
No log 95.0 475 4.3348 0.0208
No log 96.0 480 4.3296 0.0208
No log 97.0 485 4.3255 0.0208
No log 98.0 490 4.3226 0.0208
No log 99.0 495 4.3207 0.0208
6.1728 100.0 500 4.3200 0.0208

Framework versions

  • Transformers 4.34.0
  • Pytorch 2.1.0+cu121
  • Datasets 2.14.5
  • Tokenizers 0.14.1