CSE4022_NLP_EPJ_model
This model is a fine-tuned version of t5-small on the billsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.1741
- Rouge1: 0.2276
- Rouge2: 0.1147
- Rougel: 0.1939
- Rougelsum: 0.1939
- Gen Len: 19.0
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: 20
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 62 | 2.6085 | 0.1452 | 0.0463 | 0.1198 | 0.1193 | 19.0 |
No log | 2.0 | 124 | 2.4702 | 0.1683 | 0.059 | 0.1373 | 0.1372 | 19.0 |
No log | 3.0 | 186 | 2.3930 | 0.1982 | 0.0824 | 0.1636 | 0.1635 | 19.0 |
No log | 4.0 | 248 | 2.3491 | 0.2221 | 0.1036 | 0.1856 | 0.1856 | 19.0 |
No log | 5.0 | 310 | 2.3202 | 0.2281 | 0.1081 | 0.1903 | 0.1905 | 19.0 |
No log | 6.0 | 372 | 2.2934 | 0.2255 | 0.1072 | 0.1891 | 0.1892 | 19.0 |
No log | 7.0 | 434 | 2.2722 | 0.2272 | 0.111 | 0.1913 | 0.1913 | 19.0 |
No log | 8.0 | 496 | 2.2516 | 0.2284 | 0.1119 | 0.1922 | 0.1924 | 19.0 |
2.598 | 9.0 | 558 | 2.2386 | 0.2301 | 0.1133 | 0.194 | 0.1942 | 19.0 |
2.598 | 10.0 | 620 | 2.2276 | 0.229 | 0.1134 | 0.1936 | 0.1938 | 19.0 |
2.598 | 11.0 | 682 | 2.2165 | 0.2278 | 0.1145 | 0.1939 | 0.194 | 19.0 |
2.598 | 12.0 | 744 | 2.2056 | 0.2281 | 0.1147 | 0.194 | 0.1942 | 19.0 |
2.598 | 13.0 | 806 | 2.1976 | 0.2268 | 0.1143 | 0.1931 | 0.1933 | 19.0 |
2.598 | 14.0 | 868 | 2.1923 | 0.2269 | 0.1142 | 0.1939 | 0.194 | 19.0 |
2.598 | 15.0 | 930 | 2.1873 | 0.2289 | 0.1154 | 0.1952 | 0.1951 | 19.0 |
2.598 | 16.0 | 992 | 2.1805 | 0.2287 | 0.1153 | 0.1953 | 0.1953 | 19.0 |
2.3476 | 17.0 | 1054 | 2.1790 | 0.2286 | 0.1153 | 0.1951 | 0.1951 | 19.0 |
2.3476 | 18.0 | 1116 | 2.1768 | 0.2277 | 0.1146 | 0.1942 | 0.1942 | 19.0 |
2.3476 | 19.0 | 1178 | 2.1746 | 0.2278 | 0.1149 | 0.1942 | 0.1942 | 19.0 |
2.3476 | 20.0 | 1240 | 2.1741 | 0.2276 | 0.1147 | 0.1939 | 0.1939 | 19.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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