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best_model-yelp_polarity-32-42

Text Classification
Transformers
PyTorch
albert
Generated from Trainer
Inference Endpoints
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metadata
license: apache-2.0
base_model: albert-base-v2
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: best_model-yelp_polarity-32-42
    results: []

best_model-yelp_polarity-32-42

This model is a fine-tuned version of albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5674
  • Accuracy: 0.9375

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: 1e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 150

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 2 0.5344 0.9219
No log 2.0 4 0.5340 0.9219
No log 3.0 6 0.5330 0.9219
No log 4.0 8 0.5309 0.9219
0.4102 5.0 10 0.5192 0.9219
0.4102 6.0 12 0.5130 0.9219
0.4102 7.0 14 0.4996 0.9219
0.4102 8.0 16 0.4697 0.9375
0.4102 9.0 18 0.4622 0.9375
0.2817 10.0 20 0.4615 0.9375
0.2817 11.0 22 0.4620 0.9375
0.2817 12.0 24 0.4612 0.9375
0.2817 13.0 26 0.4623 0.9375
0.2817 14.0 28 0.5263 0.9219
0.064 15.0 30 0.5614 0.9219
0.064 16.0 32 0.5627 0.9219
0.064 17.0 34 0.5183 0.9219
0.064 18.0 36 0.4753 0.9375
0.064 19.0 38 0.4826 0.9375
0.002 20.0 40 0.4912 0.9375
0.002 21.0 42 0.5235 0.9219
0.002 22.0 44 0.5333 0.9219
0.002 23.0 46 0.5318 0.9219
0.002 24.0 48 0.5192 0.9219
0.0001 25.0 50 0.5060 0.9375
0.0001 26.0 52 0.4997 0.9375
0.0001 27.0 54 0.4982 0.9375
0.0001 28.0 56 0.4982 0.9375
0.0001 29.0 58 0.4984 0.9375
0.0 30.0 60 0.4987 0.9375
0.0 31.0 62 0.4989 0.9375
0.0 32.0 64 0.4992 0.9375
0.0 33.0 66 0.4994 0.9375
0.0 34.0 68 0.4997 0.9375
0.0 35.0 70 0.4999 0.9375
0.0 36.0 72 0.5002 0.9375
0.0 37.0 74 0.5005 0.9375
0.0 38.0 76 0.5009 0.9375
0.0 39.0 78 0.5012 0.9375
0.0 40.0 80 0.5016 0.9375
0.0 41.0 82 0.5020 0.9375
0.0 42.0 84 0.5024 0.9375
0.0 43.0 86 0.5029 0.9375
0.0 44.0 88 0.5033 0.9375
0.0 45.0 90 0.5038 0.9375
0.0 46.0 92 0.5043 0.9375
0.0 47.0 94 0.5047 0.9375
0.0 48.0 96 0.5052 0.9375
0.0 49.0 98 0.5057 0.9375
0.0 50.0 100 0.5062 0.9375
0.0 51.0 102 0.5068 0.9375
0.0 52.0 104 0.5073 0.9375
0.0 53.0 106 0.5078 0.9375
0.0 54.0 108 0.5083 0.9375
0.0 55.0 110 0.5089 0.9375
0.0 56.0 112 0.5094 0.9375
0.0 57.0 114 0.5100 0.9375
0.0 58.0 116 0.5105 0.9375
0.0 59.0 118 0.5110 0.9375
0.0 60.0 120 0.5116 0.9375
0.0 61.0 122 0.5122 0.9375
0.0 62.0 124 0.5128 0.9375
0.0 63.0 126 0.5133 0.9375
0.0 64.0 128 0.5139 0.9375
0.0 65.0 130 0.5145 0.9375
0.0 66.0 132 0.5150 0.9375
0.0 67.0 134 0.5156 0.9375
0.0 68.0 136 0.5161 0.9375
0.0 69.0 138 0.5166 0.9375
0.0 70.0 140 0.5172 0.9375
0.0 71.0 142 0.5177 0.9375
0.0 72.0 144 0.5182 0.9375
0.0 73.0 146 0.5188 0.9375
0.0 74.0 148 0.5193 0.9375
0.0 75.0 150 0.5199 0.9375
0.0 76.0 152 0.5204 0.9375
0.0 77.0 154 0.5210 0.9375
0.0 78.0 156 0.5216 0.9375
0.0 79.0 158 0.5222 0.9375
0.0 80.0 160 0.5228 0.9375
0.0 81.0 162 0.5233 0.9375
0.0 82.0 164 0.5239 0.9375
0.0 83.0 166 0.5245 0.9375
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0.0 86.0 172 0.5263 0.9375
0.0 87.0 174 0.5269 0.9375
0.0 88.0 176 0.5275 0.9375
0.0 89.0 178 0.5281 0.9375
0.0 90.0 180 0.5288 0.9375
0.0 91.0 182 0.5294 0.9375
0.0 92.0 184 0.5300 0.9375
0.0 93.0 186 0.5306 0.9375
0.0 94.0 188 0.5312 0.9375
0.0 95.0 190 0.5318 0.9375
0.0 96.0 192 0.5325 0.9375
0.0 97.0 194 0.5331 0.9375
0.0 98.0 196 0.5337 0.9375
0.0 99.0 198 0.5343 0.9375
0.0 100.0 200 0.5349 0.9375
0.0 101.0 202 0.5355 0.9375
0.0 102.0 204 0.5362 0.9375
0.0 103.0 206 0.5368 0.9375
0.0 104.0 208 0.5374 0.9375
0.0 105.0 210 0.5381 0.9375
0.0 106.0 212 0.5387 0.9375
0.0 107.0 214 0.5394 0.9375
0.0 108.0 216 0.5400 0.9375
0.0 109.0 218 0.5407 0.9375
0.0 110.0 220 0.5413 0.9375
0.0 111.0 222 0.5419 0.9375
0.0 112.0 224 0.5425 0.9375
0.0 113.0 226 0.5432 0.9375
0.0 114.0 228 0.5438 0.9375
0.0 115.0 230 0.5444 0.9375
0.0 116.0 232 0.5450 0.9375
0.0 117.0 234 0.5457 0.9375
0.0 118.0 236 0.5463 0.9375
0.0 119.0 238 0.5469 0.9375
0.0 120.0 240 0.5476 0.9375
0.0 121.0 242 0.5482 0.9375
0.0 122.0 244 0.5489 0.9375
0.0 123.0 246 0.5495 0.9375
0.0 124.0 248 0.5502 0.9375
0.0 125.0 250 0.5509 0.9375
0.0 126.0 252 0.5516 0.9375
0.0 127.0 254 0.5522 0.9375
0.0 128.0 256 0.5529 0.9375
0.0 129.0 258 0.5536 0.9375
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0.0 131.0 262 0.5549 0.9375
0.0 132.0 264 0.5556 0.9375
0.0 133.0 266 0.5563 0.9375
0.0 134.0 268 0.5570 0.9375
0.0 135.0 270 0.5576 0.9375
0.0 136.0 272 0.5583 0.9375
0.0 137.0 274 0.5590 0.9375
0.0 138.0 276 0.5597 0.9375
0.0 139.0 278 0.5603 0.9375
0.0 140.0 280 0.5610 0.9375
0.0 141.0 282 0.5616 0.9375
0.0 142.0 284 0.5623 0.9375
0.0 143.0 286 0.5629 0.9375
0.0 144.0 288 0.5635 0.9375
0.0 145.0 290 0.5642 0.9375
0.0 146.0 292 0.5648 0.9375
0.0 147.0 294 0.5655 0.9375
0.0 148.0 296 0.5661 0.9375
0.0 149.0 298 0.5667 0.9375
0.0 150.0 300 0.5674 0.9375

Framework versions

  • Transformers 4.32.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.4.0
  • Tokenizers 0.13.3