contract_sections_with_labels_for_text_classification_v2
This model is a fine-tuned version of google-bert/bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1120
- Accuracy: 0.9898
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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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 | Accuracy |
---|---|---|---|---|
0.0995 | 1.0 | 1000 | 0.2133 | 0.9347 |
0.0474 | 2.0 | 2000 | 0.1669 | 0.97 |
0.0334 | 3.0 | 3000 | 0.1288 | 0.9778 |
0.0263 | 4.0 | 4000 | 0.1607 | 0.9782 |
0.0214 | 5.0 | 5000 | 0.1630 | 0.9778 |
0.0226 | 6.0 | 6000 | 0.1770 | 0.9712 |
0.0179 | 7.0 | 7000 | 0.1260 | 0.9835 |
0.0128 | 8.0 | 8000 | 0.1742 | 0.9755 |
0.0166 | 9.0 | 9000 | 0.1230 | 0.9835 |
0.0185 | 10.0 | 10000 | 0.1191 | 0.9848 |
0.0139 | 11.0 | 11000 | 0.1255 | 0.984 |
0.0147 | 12.0 | 12000 | 0.1247 | 0.9855 |
0.0086 | 13.0 | 13000 | 0.1242 | 0.9852 |
0.0062 | 14.0 | 14000 | 0.1209 | 0.9858 |
0.0067 | 15.0 | 15000 | 0.1205 | 0.9852 |
0.0087 | 16.0 | 16000 | 0.1295 | 0.9838 |
0.0086 | 17.0 | 17000 | 0.1319 | 0.9835 |
0.0047 | 18.0 | 18000 | 0.1165 | 0.9855 |
0.0076 | 19.0 | 19000 | 0.1166 | 0.983 |
0.0048 | 20.0 | 20000 | 0.1227 | 0.9855 |
0.0037 | 21.0 | 21000 | 0.1216 | 0.9855 |
0.0073 | 22.0 | 22000 | 0.1157 | 0.9848 |
0.0083 | 23.0 | 23000 | 0.1193 | 0.9832 |
0.0037 | 24.0 | 24000 | 0.1090 | 0.9862 |
0.01 | 25.0 | 25000 | 0.1183 | 0.9855 |
0.0063 | 26.0 | 26000 | 0.1129 | 0.9862 |
0.006 | 27.0 | 27000 | 0.1101 | 0.986 |
0.005 | 28.0 | 28000 | 0.1155 | 0.9838 |
0.0024 | 29.0 | 29000 | 0.1005 | 0.989 |
0.0067 | 30.0 | 30000 | 0.0998 | 0.9895 |
0.0054 | 31.0 | 31000 | 0.1235 | 0.9888 |
0.0064 | 32.0 | 32000 | 0.0966 | 0.9895 |
0.003 | 33.0 | 33000 | 0.1013 | 0.9902 |
0.0032 | 34.0 | 34000 | 0.1012 | 0.9898 |
0.0033 | 35.0 | 35000 | 0.0981 | 0.9895 |
0.0044 | 36.0 | 36000 | 0.1045 | 0.9898 |
0.0029 | 37.0 | 37000 | 0.1032 | 0.99 |
0.0043 | 38.0 | 38000 | 0.1370 | 0.9848 |
0.0055 | 39.0 | 39000 | 0.1015 | 0.9902 |
0.0031 | 40.0 | 40000 | 0.1029 | 0.9898 |
0.0023 | 41.0 | 41000 | 0.1013 | 0.9895 |
0.0051 | 42.0 | 42000 | 0.0969 | 0.9895 |
0.0035 | 43.0 | 43000 | 0.1028 | 0.9895 |
0.0055 | 44.0 | 44000 | 0.1237 | 0.985 |
0.0062 | 45.0 | 45000 | 0.1087 | 0.9895 |
0.0036 | 46.0 | 46000 | 0.1016 | 0.9908 |
0.0039 | 47.0 | 47000 | 0.1023 | 0.9908 |
0.0036 | 48.0 | 48000 | 0.1039 | 0.9902 |
0.003 | 49.0 | 49000 | 0.1290 | 0.9852 |
0.0029 | 50.0 | 50000 | 0.1092 | 0.9905 |
0.0054 | 51.0 | 51000 | 0.1053 | 0.9895 |
0.002 | 52.0 | 52000 | 0.1039 | 0.9898 |
0.0056 | 53.0 | 53000 | 0.1050 | 0.9892 |
0.0032 | 54.0 | 54000 | 0.0996 | 0.99 |
0.0042 | 55.0 | 55000 | 0.1013 | 0.9895 |
0.0033 | 56.0 | 56000 | 0.0965 | 0.9902 |
0.0035 | 57.0 | 57000 | 0.1027 | 0.9898 |
0.0049 | 58.0 | 58000 | 0.1016 | 0.9898 |
0.003 | 59.0 | 59000 | 0.0992 | 0.9902 |
0.0033 | 60.0 | 60000 | 0.1005 | 0.9902 |
0.0035 | 61.0 | 61000 | 0.1045 | 0.99 |
0.004 | 62.0 | 62000 | 0.1030 | 0.9902 |
0.0038 | 63.0 | 63000 | 0.1082 | 0.9905 |
0.0013 | 64.0 | 64000 | 0.1146 | 0.9895 |
0.0046 | 65.0 | 65000 | 0.1075 | 0.9905 |
0.0028 | 66.0 | 66000 | 0.1058 | 0.99 |
0.0064 | 67.0 | 67000 | 0.1019 | 0.9898 |
0.0035 | 68.0 | 68000 | 0.1061 | 0.9895 |
0.0036 | 69.0 | 69000 | 0.1086 | 0.9895 |
0.0014 | 70.0 | 70000 | 0.1112 | 0.9895 |
0.0031 | 71.0 | 71000 | 0.1104 | 0.9902 |
0.0022 | 72.0 | 72000 | 0.1099 | 0.9902 |
0.0041 | 73.0 | 73000 | 0.1068 | 0.99 |
0.0049 | 74.0 | 74000 | 0.1088 | 0.9898 |
0.0034 | 75.0 | 75000 | 0.1100 | 0.9898 |
0.0044 | 76.0 | 76000 | 0.1111 | 0.9898 |
0.0027 | 77.0 | 77000 | 0.1096 | 0.9898 |
0.0016 | 78.0 | 78000 | 0.1096 | 0.9898 |
0.0029 | 79.0 | 79000 | 0.1023 | 0.99 |
0.005 | 80.0 | 80000 | 0.1040 | 0.9898 |
0.0034 | 81.0 | 81000 | 0.1052 | 0.9898 |
0.0027 | 82.0 | 82000 | 0.1059 | 0.9898 |
0.0032 | 83.0 | 83000 | 0.1071 | 0.9898 |
0.0022 | 84.0 | 84000 | 0.1056 | 0.9898 |
0.0029 | 85.0 | 85000 | 0.1062 | 0.9898 |
0.0028 | 86.0 | 86000 | 0.1055 | 0.9898 |
0.0036 | 87.0 | 87000 | 0.1083 | 0.9898 |
0.0038 | 88.0 | 88000 | 0.1087 | 0.9898 |
0.0021 | 89.0 | 89000 | 0.1114 | 0.9898 |
0.0035 | 90.0 | 90000 | 0.1114 | 0.9898 |
0.0033 | 91.0 | 91000 | 0.1112 | 0.9898 |
0.0053 | 92.0 | 92000 | 0.1115 | 0.9898 |
0.0034 | 93.0 | 93000 | 0.1117 | 0.9898 |
0.0029 | 94.0 | 94000 | 0.1106 | 0.9898 |
0.0038 | 95.0 | 95000 | 0.1104 | 0.9898 |
0.0032 | 96.0 | 96000 | 0.1108 | 0.9898 |
0.0042 | 97.0 | 97000 | 0.1112 | 0.9898 |
0.0028 | 98.0 | 98000 | 0.1120 | 0.9898 |
0.0044 | 99.0 | 99000 | 0.1120 | 0.9898 |
0.0033 | 100.0 | 100000 | 0.1120 | 0.9898 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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Model tree for marcelovidigal/contract_sections_with_labels_for_text_classification_v2
Base model
google-bert/bert-base-multilingual-uncased