Hugging Face's logo

Jasontth
/
climate-fever-plus-RoBERTa

Text Classification
Transformers
Safetensors
roberta
fact-checking
climate
text entailment
Inference Endpoints
Model card Files Community
climate-fever-plus-RoBERTa / README.md
Jasontth's picture
Jasontth
climate_verfication_model
9577e68
preview code
|
raw
history blame
13.8 kB
metadata
license: mit
base_model: roberta-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: results
    results: []

results

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

  • Loss: 0.7998
  • Accuracy: 0.7023
  • Precision: 0.7144
  • Recall: 0.7023
  • F1: 0.7065

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: 5e-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
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 5
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
1.0859 0.04 10 1.0722 0.6493 0.6735 0.6493 0.5118
1.0731 0.07 20 1.0562 0.6488 0.4209 0.6488 0.5105
1.0456 0.11 30 1.0316 0.6488 0.4209 0.6488 0.5105
1.0199 0.15 40 0.9979 0.6488 0.4209 0.6488 0.5105
0.9613 0.19 50 0.9362 0.6488 0.4209 0.6488 0.5105
0.8949 0.22 60 0.8645 0.6488 0.4209 0.6488 0.5105
0.9151 0.26 70 0.8606 0.6488 0.4209 0.6488 0.5105
0.8583 0.3 80 0.8593 0.6488 0.4209 0.6488 0.5105
0.9604 0.33 90 0.8539 0.6488 0.4209 0.6488 0.5105
0.7919 0.37 100 0.8504 0.6488 0.4209 0.6488 0.5105
0.9365 0.41 110 0.8520 0.6488 0.4209 0.6488 0.5105
0.9285 0.45 120 0.8521 0.6488 0.4209 0.6488 0.5105
0.8564 0.48 130 0.8615 0.6488 0.4209 0.6488 0.5105
0.8132 0.52 140 0.8583 0.6488 0.4209 0.6488 0.5105
0.8911 0.56 150 0.8467 0.6488 0.4209 0.6488 0.5105
0.8383 0.59 160 0.8373 0.6488 0.4209 0.6488 0.5105
0.8387 0.63 170 0.8372 0.6488 0.4209 0.6488 0.5105
0.979 0.67 180 0.8595 0.6488 0.4209 0.6488 0.5105
0.7621 0.71 190 0.8642 0.6488 0.4209 0.6488 0.5105
0.8367 0.74 200 0.8276 0.6553 0.6447 0.6553 0.5271
0.9116 0.78 210 0.8466 0.6493 0.6735 0.6493 0.5118
0.8444 0.82 220 0.8171 0.6504 0.6740 0.6504 0.5143
0.7815 0.86 230 0.7919 0.6667 0.6008 0.6667 0.5615
0.8592 0.89 240 0.7907 0.6732 0.5878 0.6732 0.5962
0.8933 0.93 250 0.7963 0.6813 0.6004 0.6813 0.6102
0.8409 0.97 260 0.7812 0.6797 0.6021 0.6797 0.6066
0.8285 1.0 270 0.7794 0.6737 0.5987 0.6737 0.5940
0.7895 1.04 280 0.7893 0.6846 0.6044 0.6846 0.6168
0.8012 1.08 290 0.7617 0.6813 0.6129 0.6813 0.6002
0.7215 1.12 300 0.8029 0.6748 0.6248 0.6748 0.5764
0.8134 1.15 310 0.8294 0.6781 0.5949 0.6781 0.6294
0.7247 1.19 320 0.7944 0.6732 0.5941 0.6732 0.6290
0.8043 1.23 330 0.7978 0.6656 0.5931 0.6656 0.6268
0.7647 1.26 340 0.7571 0.6884 0.6344 0.6884 0.6063
0.7807 1.3 350 0.7958 0.6412 0.6041 0.6412 0.6167
0.8031 1.34 360 0.7261 0.6906 0.6820 0.6906 0.6680
0.6965 1.38 370 0.7287 0.7003 0.6796 0.7003 0.6813
0.69 1.41 380 0.7115 0.7074 0.6981 0.7074 0.6581
0.7015 1.45 390 0.7391 0.7063 0.6932 0.7063 0.6813
0.7461 1.49 400 0.7624 0.6987 0.6791 0.6987 0.6787
0.758 1.52 410 0.7778 0.6819 0.6893 0.6819 0.6695
0.7617 1.56 420 0.7913 0.6878 0.6906 0.6878 0.6339
0.7848 1.6 430 0.7785 0.6629 0.6806 0.6629 0.6643
0.8138 1.64 440 0.7191 0.6954 0.6763 0.6954 0.6474
0.7451 1.67 450 0.7086 0.7030 0.7061 0.7030 0.6434
0.788 1.71 460 0.7202 0.6840 0.6956 0.6840 0.6497
0.7107 1.75 470 0.7543 0.6835 0.6067 0.6835 0.6379
0.7047 1.78 480 0.7940 0.6862 0.6697 0.6862 0.6258
0.8561 1.82 490 0.7497 0.6802 0.6860 0.6802 0.6666
0.804 1.86 500 0.7247 0.6938 0.6757 0.6938 0.6555
0.7796 1.9 510 0.7239 0.7063 0.6988 0.7063 0.6702
0.8124 1.93 520 0.7693 0.6976 0.7003 0.6976 0.6621
0.7306 1.97 530 0.8395 0.6363 0.6788 0.6363 0.6329
0.7079 2.01 540 0.7051 0.7041 0.6828 0.7041 0.6811
0.6018 2.04 550 0.7327 0.7058 0.6873 0.7058 0.6849
0.5824 2.08 560 0.7819 0.6743 0.6811 0.6743 0.6774
0.6001 2.12 570 0.7547 0.7139 0.6980 0.7139 0.7023
0.6471 2.16 580 0.7617 0.7172 0.7040 0.7172 0.6848
0.6226 2.19 590 0.7421 0.6927 0.6974 0.6927 0.6909
0.5203 2.23 600 0.7935 0.6694 0.6871 0.6694 0.6748
0.6445 2.27 610 0.7722 0.7182 0.7038 0.7182 0.6947
0.7027 2.3 620 0.7517 0.6754 0.7039 0.6754 0.6814
0.5662 2.34 630 0.6804 0.7182 0.7069 0.7182 0.7090
0.6304 2.38 640 0.6965 0.7128 0.6958 0.7128 0.6904
0.6258 2.42 650 0.7053 0.7041 0.7041 0.7041 0.7041
0.4966 2.45 660 0.7300 0.7177 0.7030 0.7177 0.7033
0.5721 2.49 670 0.8330 0.6683 0.6910 0.6683 0.6737
0.5507 2.53 680 0.8154 0.6857 0.7020 0.6857 0.6923
0.6392 2.57 690 0.8048 0.7166 0.7079 0.7166 0.6814
0.6128 2.6 700 0.7445 0.6786 0.6890 0.6786 0.6827
0.622 2.64 710 0.7029 0.7047 0.6895 0.7047 0.6870
0.5847 2.68 720 0.7911 0.6569 0.6889 0.6569 0.6677
0.6454 2.71 730 0.7062 0.7112 0.7017 0.7112 0.6797
0.5264 2.75 740 0.7419 0.6992 0.6893 0.6992 0.6870
0.649 2.79 750 0.7243 0.7063 0.7009 0.7063 0.7030
0.5343 2.83 760 0.7478 0.6889 0.7030 0.6889 0.6946
0.5335 2.86 770 0.7222 0.7237 0.7115 0.7237 0.7052
0.5228 2.9 780 0.7182 0.7226 0.7152 0.7226 0.7063
0.5605 2.94 790 0.7195 0.7210 0.7128 0.7210 0.7106
0.627 2.97 800 0.7559 0.6878 0.7135 0.6878 0.6933
0.6536 3.01 810 0.6616 0.7275 0.7141 0.7275 0.7105
0.4106 3.05 820 0.7176 0.7307 0.7209 0.7307 0.7230
0.3588 3.09 830 0.8387 0.7226 0.7230 0.7226 0.7183
0.404 3.12 840 0.8459 0.7117 0.7138 0.7117 0.7124
0.4313 3.16 850 0.8406 0.6992 0.7108 0.6992 0.7036
0.3407 3.2 860 0.8317 0.6916 0.7133 0.6916 0.6997
0.365 3.23 870 0.8310 0.6992 0.7110 0.6992 0.7035
0.3776 3.27 880 0.8376 0.6927 0.7107 0.6927 0.6986
0.3442 3.31 890 0.8554 0.7079 0.7082 0.7079 0.7079
0.41 3.35 900 0.9473 0.6401 0.7039 0.6401 0.6550
0.4649 3.38 910 0.8139 0.7134 0.7063 0.7134 0.7090
0.4359 3.42 920 0.8275 0.6992 0.7095 0.6992 0.7022
0.2906 3.46 930 0.8398 0.7096 0.7013 0.7096 0.7025
0.413 3.49 940 0.8558 0.6982 0.7049 0.6982 0.7009
0.3936 3.53 950 0.8457 0.7025 0.7058 0.7025 0.7039
0.3691 3.57 960 0.8312 0.7014 0.7102 0.7014 0.7050
0.3747 3.61 970 0.8146 0.7210 0.7074 0.7210 0.7086
0.4037 3.64 980 0.7906 0.7199 0.7132 0.7199 0.7150
0.4112 3.68 990 0.8135 0.7139 0.7145 0.7139 0.7137
0.3685 3.72 1000 0.8024 0.7106 0.7144 0.7106 0.7123
0.3881 3.75 1010 0.8339 0.7063 0.7109 0.7063 0.7063
0.4168 3.79 1020 0.8261 0.7231 0.7191 0.7231 0.7206
0.3591 3.83 1030 0.8014 0.7340 0.7258 0.7340 0.7281
0.3632 3.87 1040 0.8568 0.6878 0.7206 0.6878 0.6974
0.259 3.9 1050 0.8182 0.7324 0.7226 0.7324 0.7225
0.3741 3.94 1060 0.8511 0.7009 0.7200 0.7009 0.7078
0.3551 3.98 1070 0.8283 0.7150 0.7186 0.7150 0.7159
0.4105 4.01 1080 0.7817 0.7204 0.7209 0.7204 0.7205
0.2411 4.05 1090 0.8384 0.7372 0.7272 0.7372 0.7274
0.2166 4.09 1100 0.9466 0.7003 0.7240 0.7003 0.7066
0.4075 4.13 1110 0.9255 0.6976 0.7157 0.6976 0.7042
0.3328 4.16 1120 0.9120 0.6922 0.7153 0.6922 0.7003
0.1584 4.2 1130 0.9688 0.6857 0.7100 0.6857 0.6942
0.1737 4.24 1140 1.0205 0.7356 0.7267 0.7356 0.7289
0.2335 4.28 1150 1.0734 0.7068 0.7194 0.7068 0.7116
0.2179 4.31 1160 1.0748 0.7085 0.7190 0.7085 0.7127
0.244 4.35 1170 1.0801 0.7030 0.7220 0.7030 0.7097
0.2151 4.39 1180 1.0332 0.7112 0.7176 0.7112 0.7140
0.2602 4.42 1190 1.0343 0.7134 0.7181 0.7134 0.7154
0.131 4.46 1200 1.0453 0.7128 0.7175 0.7128 0.7149
0.1966 4.5 1210 1.0673 0.7096 0.7160 0.7096 0.7121
0.2136 4.54 1220 1.0550 0.7166 0.7157 0.7166 0.7158
0.1625 4.57 1230 1.0690 0.7172 0.7148 0.7172 0.7156
0.2199 4.61 1240 1.0908 0.7112 0.7182 0.7112 0.7141
0.2028 4.65 1250 1.0991 0.7085 0.7200 0.7085 0.7130
0.2669 4.68 1260 1.0944 0.7134 0.7205 0.7134 0.7163
0.1408 4.72 1270 1.0827 0.7248 0.7198 0.7248 0.7215
0.2649 4.76 1280 1.0974 0.7199 0.7182 0.7199 0.7187
0.1512 4.8 1290 1.1159 0.7220 0.7212 0.7220 0.7214
0.1962 4.83 1300 1.1374 0.7161 0.7206 0.7161 0.7180
0.2322 4.87 1310 1.1435 0.7144 0.7226 0.7144 0.7178
0.2095 4.91 1320 1.1408 0.7106 0.7220 0.7106 0.7151
0.1534 4.94 1330 1.1466 0.7123 0.7248 0.7123 0.7170
0.2505 4.98 1340 1.1481 0.7123 0.7248 0.7123 0.7170

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0