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t5-fine-tuned-with-25-yake-keywords
This model is a fine-tuned version of t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7255
- Rouge1: 25.5531
- Rouge2: 11.1657
- Rougel: 20.7513
- Rougelsum: 24.054
- 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.3097 | 1.0 | 604 | 1.3789 | 25.5146 | 11.2077 | 20.8249 | 23.9199 | 19.0 |
| 1.1951 | 2.0 | 1208 | 1.3779 | 25.3347 | 11.2485 | 20.6781 | 23.7106 | 19.0 |
| 1.1081 | 3.0 | 1812 | 1.3903 | 26.1109 | 11.8345 | 21.2205 | 24.551 | 18.994 |
| 1.0272 | 4.0 | 2416 | 1.4042 | 26.027 | 11.5618 | 21.1159 | 24.3576 | 18.992 |
| 0.919 | 5.0 | 3020 | 1.4225 | 25.8294 | 11.5972 | 21.0053 | 24.3003 | 18.992 |
| 0.8643 | 6.0 | 3624 | 1.4410 | 25.9719 | 11.6151 | 21.0454 | 24.4411 | 18.99 |
| 0.8215 | 7.0 | 4228 | 1.4599 | 25.68 | 11.2692 | 20.9075 | 24.2681 | 19.0 |
| 0.7931 | 8.0 | 4832 | 1.4926 | 25.0808 | 10.9178 | 20.4053 | 23.6258 | 19.0 |
| 0.7664 | 9.0 | 5436 | 1.5090 | 25.458 | 10.9978 | 20.6381 | 23.9113 | 19.0 |
| 0.7053 | 10.0 | 6040 | 1.5259 | 25.4787 | 10.8938 | 20.5842 | 23.9459 | 18.998 |
| 0.6725 | 11.0 | 6644 | 1.5481 | 25.2993 | 10.7172 | 20.5288 | 23.8319 | 19.0 |
| 0.6462 | 12.0 | 7248 | 1.5710 | 25.6251 | 11.0816 | 20.7758 | 24.082 | 19.0 |
| 0.6275 | 13.0 | 7852 | 1.5884 | 25.8573 | 11.0737 | 20.988 | 24.294 | 19.0 |
| 0.5838 | 14.0 | 8456 | 1.6131 | 26.1096 | 11.3973 | 21.3659 | 24.6114 | 19.0 |
| 0.5682 | 15.0 | 9060 | 1.6259 | 25.7213 | 11.1484 | 20.8604 | 24.1114 | 19.0 |
| 0.5629 | 16.0 | 9664 | 1.6473 | 25.6197 | 11.2045 | 20.8956 | 24.1237 | 19.0 |
| 0.5446 | 17.0 | 10268 | 1.6645 | 25.4284 | 10.7362 | 20.4946 | 23.9147 | 19.0 |
| 0.5108 | 18.0 | 10872 | 1.6716 | 25.6986 | 11.2317 | 20.8851 | 24.272 | 19.0 |
| 0.5358 | 19.0 | 11476 | 1.6882 | 25.8002 | 11.2396 | 21.0001 | 24.2643 | 19.0 |
| 0.4959 | 20.0 | 12080 | 1.7027 | 25.636 | 11.2417 | 20.8785 | 24.1355 | 18.992 |
| 0.4942 | 21.0 | 12684 | 1.7131 | 25.6154 | 11.1795 | 20.7925 | 24.1343 | 19.0 |
| 0.4833 | 22.0 | 13288 | 1.7178 | 25.7708 | 11.2434 | 20.9096 | 24.1974 | 19.0 |
| 0.4702 | 23.0 | 13892 | 1.7227 | 25.6977 | 11.2352 | 20.9147 | 24.1121 | 19.0 |
| 0.4747 | 24.0 | 14496 | 1.7241 | 25.6248 | 11.2042 | 20.8192 | 24.1186 | 19.0 |
| 0.4691 | 25.0 | 15100 | 1.7255 | 25.5531 | 11.1657 | 20.7513 | 24.054 | 19.0 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
