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dialogpt-medium-ear_1-hs_cn_decay
This model is a fine-tuned version of microsoft/DialoGPT-medium on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5666
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: 4
- eval_batch_size: 4
- seed: 21
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 6.3092 | 0.01 | 10 | 9.8250 |
| 5.7405 | 0.02 | 20 | 8.9631 |
| 2.3101 | 0.03 | 30 | 4.2371 |
| -1.1908 | 0.04 | 40 | 1.2645 |
| -1.8271 | 0.05 | 50 | 1.0242 |
| -1.6416 | 0.06 | 60 | 0.9279 |
| -1.8192 | 0.07 | 70 | 0.8478 |
| -1.8256 | 0.08 | 80 | 0.7994 |
| -1.9314 | 0.09 | 90 | 0.7673 |
| -1.8831 | 0.1 | 100 | 0.7432 |
| -1.7094 | 0.11 | 110 | 0.7269 |
| -1.8073 | 0.12 | 120 | 0.7155 |
| -1.8911 | 0.13 | 130 | 0.7037 |
| -1.786 | 0.14 | 140 | 0.6932 |
| -2.0278 | 0.15 | 150 | 0.6846 |
| -1.7418 | 0.16 | 160 | 0.6769 |
| -2.0351 | 0.17 | 170 | 0.6691 |
| -1.8694 | 0.18 | 180 | 0.6612 |
| -1.7626 | 0.19 | 190 | 0.6551 |
| -1.7849 | 0.2 | 200 | 0.6492 |
| -2.0599 | 0.21 | 210 | 0.6446 |
| -1.9591 | 0.22 | 220 | 0.6401 |
| -1.9246 | 0.23 | 230 | 0.6359 |
| -1.8881 | 0.24 | 240 | 0.6334 |
| -1.9835 | 0.25 | 250 | 0.6306 |
| -1.8657 | 0.26 | 260 | 0.6264 |
| -1.9111 | 0.27 | 270 | 0.6225 |
| -1.9939 | 0.28 | 280 | 0.6198 |
| -2.0166 | 0.29 | 290 | 0.6170 |
| -1.755 | 0.3 | 300 | 0.6144 |
| -1.8769 | 0.31 | 310 | 0.6118 |
| -1.9875 | 0.32 | 320 | 0.6107 |
| -1.8674 | 0.33 | 330 | 0.6091 |
| -1.8181 | 0.34 | 340 | 0.6079 |
| -1.8287 | 0.35 | 350 | 0.6071 |
| -1.8231 | 0.36 | 360 | 0.6043 |
| -1.745 | 0.37 | 370 | 0.6030 |
| -1.7558 | 0.38 | 380 | 0.6011 |
| -1.9552 | 0.39 | 390 | 0.6009 |
| -1.7529 | 0.4 | 400 | 0.5994 |
| -1.8206 | 0.41 | 410 | 0.5984 |
| -1.7374 | 0.42 | 420 | 0.5972 |
| -1.6562 | 0.43 | 430 | 0.5952 |
| -1.6346 | 0.44 | 440 | 0.5932 |
| -1.7629 | 0.45 | 450 | 0.5933 |
| -1.8789 | 0.46 | 460 | 0.5939 |
| -1.7258 | 0.47 | 470 | 0.5912 |
| -1.8586 | 0.48 | 480 | 0.5896 |
| -1.8896 | 0.49 | 490 | 0.5890 |
| -1.7129 | 0.5 | 500 | 0.5876 |
| -1.7824 | 0.51 | 510 | 0.5860 |
| -1.725 | 0.52 | 520 | 0.5855 |
| -1.7602 | 0.53 | 530 | 0.5849 |
| -1.6211 | 0.54 | 540 | 0.5848 |
| -1.8583 | 0.55 | 550 | 0.5842 |
| -1.5637 | 0.56 | 560 | 0.5832 |
| -1.5247 | 0.57 | 570 | 0.5830 |
| -1.7575 | 0.58 | 580 | 0.5818 |
| -1.6036 | 0.59 | 590 | 0.5809 |
| -1.7476 | 0.6 | 600 | 0.5802 |
| -1.5963 | 0.61 | 610 | 0.5784 |
| -1.6185 | 0.62 | 620 | 0.5778 |
| -1.543 | 0.63 | 630 | 0.5770 |
| -1.4096 | 0.64 | 640 | 0.5765 |
| -1.6566 | 0.65 | 650 | 0.5771 |
| -1.6998 | 0.66 | 660 | 0.5765 |
| -1.5556 | 0.67 | 670 | 0.5762 |
| -1.5735 | 0.68 | 680 | 0.5756 |
| -1.4755 | 0.69 | 690 | 0.5750 |
| -1.631 | 0.7 | 700 | 0.5756 |
| -1.4281 | 0.71 | 710 | 0.5751 |
| -1.5514 | 0.72 | 720 | 0.5739 |
| -1.4284 | 0.73 | 730 | 0.5736 |
| -1.5609 | 0.74 | 740 | 0.5729 |
| -1.5762 | 0.75 | 750 | 0.5727 |
| -1.5067 | 0.76 | 760 | 0.5719 |
| -1.4276 | 0.77 | 770 | 0.5710 |
| -1.4509 | 0.78 | 780 | 0.5707 |
| -1.5881 | 0.79 | 790 | 0.5699 |
| -1.5085 | 0.8 | 800 | 0.5696 |
| -1.5048 | 0.81 | 810 | 0.5694 |
| -1.4063 | 0.82 | 820 | 0.5694 |
| -1.6457 | 0.83 | 830 | 0.5689 |
| -1.357 | 0.84 | 840 | 0.5683 |
| -1.5625 | 0.85 | 850 | 0.5684 |
| -1.3136 | 0.86 | 860 | 0.5680 |
| -1.3961 | 0.87 | 870 | 0.5669 |
| -1.322 | 0.88 | 880 | 0.5664 |
| -1.3932 | 0.89 | 890 | 0.5662 |
| -1.3923 | 0.9 | 900 | 0.5665 |
| -1.4139 | 0.91 | 910 | 0.5675 |
| -1.4337 | 0.92 | 920 | 0.5666 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.11.0+cu113
- Datasets 2.11.0
- Tokenizers 0.12.1
