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topicalchat-multiturn
This model is a fine-tuned version of microsoft/DialoGPT-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.5260
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 1.0 | 73 | 4.2992 |
No log | 2.0 | 146 | 3.4433 |
No log | 3.0 | 219 | 3.1606 |
No log | 4.0 | 292 | 3.0366 |
No log | 5.0 | 365 | 2.9679 |
No log | 6.0 | 438 | 2.9131 |
4.1401 | 7.0 | 511 | 2.8752 |
4.1401 | 8.0 | 584 | 2.8391 |
4.1401 | 9.0 | 657 | 2.8118 |
4.1401 | 10.0 | 730 | 2.7871 |
4.1401 | 11.0 | 803 | 2.7659 |
4.1401 | 12.0 | 876 | 2.7489 |
4.1401 | 13.0 | 949 | 2.7331 |
2.9768 | 14.0 | 1022 | 2.7196 |
2.9768 | 15.0 | 1095 | 2.7071 |
2.9768 | 16.0 | 1168 | 2.6940 |
2.9768 | 17.0 | 1241 | 2.6854 |
2.9768 | 18.0 | 1314 | 2.6728 |
2.9768 | 19.0 | 1387 | 2.6647 |
2.9768 | 20.0 | 1460 | 2.6562 |
2.7864 | 21.0 | 1533 | 2.6482 |
2.7864 | 22.0 | 1606 | 2.6439 |
2.7864 | 23.0 | 1679 | 2.6326 |
2.7864 | 24.0 | 1752 | 2.6107 |
2.7864 | 25.0 | 1825 | 2.6043 |
2.7864 | 26.0 | 1898 | 2.5970 |
2.7864 | 27.0 | 1971 | 2.5908 |
2.6568 | 28.0 | 2044 | 2.5862 |
2.6568 | 29.0 | 2117 | 2.5828 |
2.6568 | 30.0 | 2190 | 2.5765 |
2.6568 | 31.0 | 2263 | 2.5742 |
2.6568 | 32.0 | 2336 | 2.5682 |
2.6568 | 33.0 | 2409 | 2.5656 |
2.6568 | 34.0 | 2482 | 2.5614 |
2.5489 | 35.0 | 2555 | 2.5605 |
2.5489 | 36.0 | 2628 | 2.5552 |
2.5489 | 37.0 | 2701 | 2.5541 |
2.5489 | 38.0 | 2774 | 2.5494 |
2.5489 | 39.0 | 2847 | 2.5491 |
2.5489 | 40.0 | 2920 | 2.5455 |
2.5489 | 41.0 | 2993 | 2.5452 |
2.475 | 42.0 | 3066 | 2.5433 |
2.475 | 43.0 | 3139 | 2.5397 |
2.475 | 44.0 | 3212 | 2.5386 |
2.475 | 45.0 | 3285 | 2.5400 |
2.475 | 46.0 | 3358 | 2.5339 |
2.475 | 47.0 | 3431 | 2.5327 |
2.4144 | 48.0 | 3504 | 2.5327 |
2.4144 | 49.0 | 3577 | 2.5312 |
2.4144 | 50.0 | 3650 | 2.5338 |
2.4144 | 51.0 | 3723 | 2.5314 |
2.4144 | 52.0 | 3796 | 2.5309 |
2.4144 | 53.0 | 3869 | 2.5289 |
2.4144 | 54.0 | 3942 | 2.5290 |
2.3642 | 55.0 | 4015 | 2.5270 |
2.3642 | 56.0 | 4088 | 2.5270 |
2.3642 | 57.0 | 4161 | 2.5263 |
2.3642 | 58.0 | 4234 | 2.5267 |
2.3642 | 59.0 | 4307 | 2.5273 |
2.3642 | 60.0 | 4380 | 2.5258 |
2.3642 | 61.0 | 4453 | 2.5253 |
2.3216 | 62.0 | 4526 | 2.5244 |
2.3216 | 63.0 | 4599 | 2.5256 |
2.3216 | 64.0 | 4672 | 2.5227 |
2.3216 | 65.0 | 4745 | 2.5241 |
2.3216 | 66.0 | 4818 | 2.5244 |
2.3216 | 67.0 | 4891 | 2.5236 |
2.3216 | 68.0 | 4964 | 2.5251 |
2.2879 | 69.0 | 5037 | 2.5231 |
2.2879 | 70.0 | 5110 | 2.5254 |
2.2879 | 71.0 | 5183 | 2.5242 |
2.2879 | 72.0 | 5256 | 2.5254 |
2.2879 | 73.0 | 5329 | 2.5253 |
2.2879 | 74.0 | 5402 | 2.5228 |
2.2879 | 75.0 | 5475 | 2.5247 |
2.261 | 76.0 | 5548 | 2.5243 |
2.261 | 77.0 | 5621 | 2.5247 |
2.261 | 78.0 | 5694 | 2.5250 |
2.261 | 79.0 | 5767 | 2.5248 |
2.261 | 80.0 | 5840 | 2.5236 |
2.261 | 81.0 | 5913 | 2.5264 |
2.261 | 82.0 | 5986 | 2.5249 |
2.2396 | 83.0 | 6059 | 2.5256 |
2.2396 | 84.0 | 6132 | 2.5267 |
2.2396 | 85.0 | 6205 | 2.5258 |
2.2396 | 86.0 | 6278 | 2.5242 |
2.2396 | 87.0 | 6351 | 2.5233 |
2.2396 | 88.0 | 6424 | 2.5249 |
2.2396 | 89.0 | 6497 | 2.5253 |
2.2238 | 90.0 | 6570 | 2.5252 |
2.2238 | 91.0 | 6643 | 2.5255 |
2.2238 | 92.0 | 6716 | 2.5263 |
2.2238 | 93.0 | 6789 | 2.5261 |
2.2238 | 94.0 | 6862 | 2.5257 |
2.2238 | 95.0 | 6935 | 2.5253 |
2.213 | 96.0 | 7008 | 2.5267 |
2.213 | 97.0 | 7081 | 2.5258 |
2.213 | 98.0 | 7154 | 2.5258 |
2.213 | 99.0 | 7227 | 2.5259 |
2.213 | 100.0 | 7300 | 2.5260 |
Framework versions
- Transformers 4.8.1
- Pytorch 1.8.1+cu111
- Datasets 1.8.0
- Tokenizers 0.10.3
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