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bert-base-uncased-sst-2-32-13

Text Classification
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PyTorch
bert
Generated from Trainer
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metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: bert-base-uncased-sst-2-32-13
    results: []

bert-base-uncased-sst-2-32-13

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

  • Loss: 1.5606
  • Accuracy: 0.625

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: 50
  • num_epochs: 150

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 2 0.6827 0.6875
No log 2.0 4 0.6826 0.6875
No log 3.0 6 0.6822 0.7031
No log 4.0 8 0.6818 0.6719
0.6948 5.0 10 0.6812 0.6719
0.6948 6.0 12 0.6805 0.6406
0.6948 7.0 14 0.6797 0.6406
0.6948 8.0 16 0.6789 0.6406
0.6948 9.0 18 0.6779 0.6562
0.6864 10.0 20 0.6768 0.6562
0.6864 11.0 22 0.6755 0.6562
0.6864 12.0 24 0.6741 0.6875
0.6864 13.0 26 0.6726 0.6719
0.6864 14.0 28 0.6710 0.6719
0.6517 15.0 30 0.6694 0.7031
0.6517 16.0 32 0.6676 0.6875
0.6517 17.0 34 0.6657 0.6719
0.6517 18.0 36 0.6643 0.625
0.6517 19.0 38 0.6636 0.6094
0.6027 20.0 40 0.6642 0.5938
0.6027 21.0 42 0.6632 0.5781
0.6027 22.0 44 0.6607 0.5781
0.6027 23.0 46 0.6582 0.6094
0.6027 24.0 48 0.6562 0.6406
0.4998 25.0 50 0.6546 0.6094
0.4998 26.0 52 0.6503 0.5938
0.4998 27.0 54 0.6450 0.6094
0.4998 28.0 56 0.6395 0.6094
0.4998 29.0 58 0.6362 0.5938
0.3593 30.0 60 0.6380 0.5938
0.3593 31.0 62 0.6361 0.5938
0.3593 32.0 64 0.6348 0.5938
0.3593 33.0 66 0.6327 0.625
0.3593 34.0 68 0.6301 0.6094
0.2483 35.0 70 0.6347 0.6094
0.2483 36.0 72 0.6401 0.5938
0.2483 37.0 74 0.6468 0.5781
0.2483 38.0 76 0.6533 0.5781
0.2483 39.0 78 0.6600 0.5938
0.1735 40.0 80 0.6621 0.5938
0.1735 41.0 82 0.6652 0.5938
0.1735 42.0 84 0.6745 0.6094
0.1735 43.0 86 0.6849 0.6094
0.1735 44.0 88 0.6956 0.5938
0.111 45.0 90 0.7087 0.5938
0.111 46.0 92 0.7238 0.5938
0.111 47.0 94 0.7376 0.5938
0.111 48.0 96 0.7506 0.5938
0.111 49.0 98 0.7646 0.6094
0.0691 50.0 100 0.7817 0.6094
0.0691 51.0 102 0.8015 0.625
0.0691 52.0 104 0.8277 0.625
0.0691 53.0 106 0.8582 0.625
0.0691 54.0 108 0.8849 0.625
0.0395 55.0 110 0.9094 0.625
0.0395 56.0 112 0.9309 0.625
0.0395 57.0 114 0.9525 0.625
0.0395 58.0 116 0.9740 0.6094
0.0395 59.0 118 0.9959 0.6094
0.0213 60.0 120 1.0209 0.6094
0.0213 61.0 122 1.0452 0.625
0.0213 62.0 124 1.0680 0.625
0.0213 63.0 126 1.0908 0.625
0.0213 64.0 128 1.1149 0.6094
0.0129 65.0 130 1.1381 0.625
0.0129 66.0 132 1.1590 0.625
0.0129 67.0 134 1.1787 0.625
0.0129 68.0 136 1.1960 0.625
0.0129 69.0 138 1.2125 0.625
0.0093 70.0 140 1.2267 0.625
0.0093 71.0 142 1.2399 0.625
0.0093 72.0 144 1.2516 0.625
0.0093 73.0 146 1.2626 0.625
0.0093 74.0 148 1.2726 0.6406
0.0071 75.0 150 1.2825 0.6406
0.0071 76.0 152 1.2921 0.625
0.0071 77.0 154 1.3016 0.625
0.0071 78.0 156 1.3104 0.625
0.0071 79.0 158 1.3177 0.625
0.0059 80.0 160 1.3243 0.625
0.0059 81.0 162 1.3311 0.625
0.0059 82.0 164 1.3377 0.625
0.0059 83.0 166 1.3446 0.625
0.0059 84.0 168 1.3519 0.625
0.0051 85.0 170 1.3590 0.625
0.0051 86.0 172 1.3662 0.625
0.0051 87.0 174 1.3731 0.625
0.0051 88.0 176 1.3801 0.625
0.0051 89.0 178 1.3867 0.625
0.0045 90.0 180 1.3929 0.625
0.0045 91.0 182 1.3988 0.625
0.0045 92.0 184 1.4048 0.625
0.0045 93.0 186 1.4110 0.625
0.0045 94.0 188 1.4171 0.625
0.0042 95.0 190 1.4231 0.625
0.0042 96.0 192 1.4290 0.625
0.0042 97.0 194 1.4346 0.625
0.0042 98.0 196 1.4401 0.625
0.0042 99.0 198 1.4454 0.625
0.0037 100.0 200 1.4506 0.625
0.0037 101.0 202 1.4555 0.625
0.0037 102.0 204 1.4604 0.625
0.0037 103.0 206 1.4650 0.625
0.0037 104.0 208 1.4690 0.625
0.0034 105.0 210 1.4728 0.625
0.0034 106.0 212 1.4765 0.625
0.0034 107.0 214 1.4802 0.625
0.0034 108.0 216 1.4836 0.625
0.0034 109.0 218 1.4870 0.625
0.0033 110.0 220 1.4903 0.625
0.0033 111.0 222 1.4936 0.625
0.0033 112.0 224 1.4969 0.625
0.0033 113.0 226 1.5002 0.625
0.0033 114.0 228 1.5036 0.625
0.0031 115.0 230 1.5069 0.625
0.0031 116.0 232 1.5100 0.625
0.0031 117.0 234 1.5130 0.625
0.0031 118.0 236 1.5161 0.625
0.0031 119.0 238 1.5190 0.625
0.003 120.0 240 1.5216 0.625
0.003 121.0 242 1.5242 0.625
0.003 122.0 244 1.5269 0.625
0.003 123.0 246 1.5295 0.625
0.003 124.0 248 1.5321 0.625
0.0028 125.0 250 1.5345 0.625
0.0028 126.0 252 1.5367 0.625
0.0028 127.0 254 1.5386 0.625
0.0028 128.0 256 1.5405 0.625
0.0028 129.0 258 1.5422 0.625
0.0027 130.0 260 1.5438 0.625
0.0027 131.0 262 1.5453 0.625
0.0027 132.0 264 1.5468 0.625
0.0027 133.0 266 1.5482 0.625
0.0027 134.0 268 1.5495 0.625
0.0027 135.0 270 1.5507 0.625
0.0027 136.0 272 1.5518 0.625
0.0027 137.0 274 1.5529 0.625
0.0027 138.0 276 1.5539 0.625
0.0027 139.0 278 1.5549 0.625
0.0026 140.0 280 1.5557 0.625
0.0026 141.0 282 1.5565 0.625
0.0026 142.0 284 1.5573 0.625
0.0026 143.0 286 1.5580 0.625
0.0026 144.0 288 1.5587 0.625
0.0025 145.0 290 1.5593 0.625
0.0025 146.0 292 1.5597 0.625
0.0025 147.0 294 1.5601 0.625
0.0025 148.0 296 1.5603 0.625
0.0025 149.0 298 1.5605 0.625
0.0026 150.0 300 1.5606 0.625

Framework versions

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