Etelis / TweetEval_BERT_5E

huggingface.co
Total runs: 7
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7-day runs: 1
30-day runs: -3
Model's Last Updated: November 29 2022
text-classification

Introduction of TweetEval_BERT_5E

Model Details of TweetEval_BERT_5E

TweetEval_BERT_5E

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

  • Loss: 0.5419
  • Accuracy: 0.9267
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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5
Training results
Training Loss Epoch Step Validation Loss Accuracy
0.6264 0.04 50 0.5266 0.74
0.5054 0.08 100 0.5959 0.6333
0.4732 0.12 150 0.3524 0.86
0.3916 0.16 200 0.3195 0.8667
0.3477 0.2 250 0.2878 0.8867
0.3116 0.24 300 0.2903 0.92
0.3039 0.28 350 0.2488 0.8933
0.2633 0.32 400 0.2530 0.92
0.2667 0.37 450 0.2125 0.9267
0.2604 0.41 500 0.2628 0.8867
0.278 0.45 550 0.2322 0.8867
0.2625 0.49 600 0.1903 0.92
0.2808 0.53 650 0.2400 0.8933
0.2396 0.57 700 0.2184 0.9067
0.2571 0.61 750 0.1906 0.9133
0.2676 0.65 800 0.2467 0.9067
0.2288 0.69 850 0.2038 0.9133
0.2959 0.73 900 0.1941 0.9
0.2619 0.77 950 0.2100 0.9333
0.2504 0.81 1000 0.1523 0.9333
0.2338 0.85 1050 0.1429 0.94
0.2529 0.89 1100 0.1269 0.94
0.2238 0.93 1150 0.1722 0.9333
0.2295 0.97 1200 0.1874 0.94
0.2089 1.01 1250 0.2214 0.9067
0.1406 1.06 1300 0.3410 0.9133
0.1587 1.1 1350 0.3330 0.9133
0.1732 1.14 1400 0.2716 0.9133
0.195 1.18 1450 0.3726 0.92
0.1777 1.22 1500 0.2430 0.9267
0.1433 1.26 1550 0.3011 0.9267
0.1333 1.3 1600 0.2489 0.9333
0.1516 1.34 1650 0.3340 0.9267
0.1774 1.38 1700 0.2497 0.8933
0.1608 1.42 1750 0.3234 0.9
0.1534 1.46 1800 0.3383 0.9133
0.1287 1.5 1850 0.3134 0.9133
0.1422 1.54 1900 0.3330 0.9
0.1578 1.58 1950 0.3281 0.9133
0.1786 1.62 2000 0.2939 0.9267
0.2019 1.66 2050 0.3535 0.9
0.1995 1.7 2100 0.3032 0.9067
0.159 1.75 2150 0.2598 0.9267
0.1493 1.79 2200 0.2391 0.9267
0.1748 1.83 2250 0.2258 0.92
0.1783 1.87 2300 0.2749 0.9133
0.1619 1.91 2350 0.2699 0.92
0.1378 1.95 2400 0.2776 0.9067
0.1529 1.99 2450 0.2235 0.9333
0.1071 2.03 2500 0.2841 0.9267
0.0812 2.07 2550 0.3178 0.9267
0.0464 2.11 2600 0.3567 0.92
0.1108 2.15 2650 0.2723 0.92
0.0845 2.19 2700 0.2774 0.9267
0.0795 2.23 2750 0.3027 0.9267
0.0403 2.27 2800 0.3566 0.9267
0.0664 2.31 2850 0.4015 0.92
0.0659 2.35 2900 0.4298 0.9067
0.1059 2.39 2950 0.4028 0.92
0.105 2.44 3000 0.3701 0.92
0.0808 2.48 3050 0.3206 0.9267
0.0811 2.52 3100 0.3644 0.9133
0.0458 2.56 3150 0.3781 0.9267
0.0764 2.6 3200 0.3749 0.9267
0.0567 2.64 3250 0.3995 0.92
0.0971 2.68 3300 0.3455 0.92
0.0579 2.72 3350 0.4508 0.92
0.0853 2.76 3400 0.4350 0.92
0.0577 2.8 3450 0.3804 0.9333
0.0732 2.84 3500 0.4387 0.92
0.0874 2.88 3550 0.3885 0.9333
0.1031 2.92 3600 0.3937 0.92
0.0335 2.96 3650 0.4963 0.8933
0.0913 3.0 3700 0.3827 0.9333
0.047 3.04 3750 0.4136 0.92
0.0531 3.08 3800 0.4362 0.92
0.0265 3.12 3850 0.4857 0.92
0.038 3.17 3900 0.4425 0.92
0.0294 3.21 3950 0.4347 0.92
0.0367 3.25 4000 0.4291 0.9333
0.0102 3.29 4050 0.5178 0.9267
0.0311 3.33 4100 0.4784 0.9267
0.0274 3.37 4150 0.5421 0.9267
0.0275 3.41 4200 0.5194 0.92
0.0795 3.45 4250 0.4788 0.92
0.0413 3.49 4300 0.4393 0.9267
0.0373 3.53 4350 0.4965 0.92
0.0303 3.57 4400 0.4284 0.9267
0.0248 3.61 4450 0.4476 0.9267
0.0557 3.65 4500 0.4690 0.92
0.0358 3.69 4550 0.4774 0.9133
0.0194 3.73 4600 0.4755 0.92
0.0473 3.77 4650 0.4637 0.92
0.0133 3.81 4700 0.4868 0.92
0.0204 3.86 4750 0.4886 0.9267
0.0338 3.9 4800 0.5101 0.9267
0.0424 3.94 4850 0.4812 0.9267
0.0237 3.98 4900 0.4837 0.9267
0.0372 4.02 4950 0.5000 0.9267
0.0254 4.06 5000 0.5210 0.92
0.024 4.1 5050 0.5272 0.92
0.0117 4.14 5100 0.5447 0.92
0.018 4.18 5150 0.5353 0.92
0.0097 4.22 5200 0.5415 0.9267
0.0151 4.26 5250 0.5447 0.9267
0.0118 4.3 5300 0.5285 0.9267
0.0004 4.34 5350 0.5399 0.9267
0.0102 4.38 5400 0.5552 0.9267
0.0012 4.42 5450 0.5689 0.92
0.02 4.46 5500 0.5619 0.9267
0.0056 4.5 5550 0.5784 0.92
0.0271 4.55 5600 0.5766 0.92
0.0191 4.59 5650 0.5662 0.92
0.0311 4.63 5700 0.5514 0.9267
0.0167 4.67 5750 0.5510 0.9267
0.0293 4.71 5800 0.5571 0.9267
0.0304 4.75 5850 0.5494 0.92
0.0161 4.79 5900 0.5469 0.9267
0.0017 4.83 5950 0.5468 0.9267
0.0176 4.87 6000 0.5426 0.9267
0.0094 4.91 6050 0.5402 0.9267
0.0041 4.95 6100 0.5416 0.9267
0.0281 4.99 6150 0.5419 0.9267
Framework versions
  • Transformers 4.24.0
  • Pytorch 1.13.0
  • Datasets 2.3.2
  • Tokenizers 0.13.2

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More Information About TweetEval_BERT_5E huggingface.co Model

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TweetEval_BERT_5E huggingface.co

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