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qwen-text-linear
This model is a fine-tuned version of Qwen/Qwen-14B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.4786
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-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.4229 | 0.01 | 10 | 2.4927 |
2.4139 | 0.03 | 20 | 2.4927 |
2.4284 | 0.04 | 30 | 2.4926 |
2.4523 | 0.05 | 40 | 2.4923 |
2.4364 | 0.06 | 50 | 2.4920 |
2.4522 | 0.08 | 60 | 2.4916 |
2.5044 | 0.09 | 70 | 2.4910 |
2.442 | 0.1 | 80 | 2.4903 |
2.387 | 0.12 | 90 | 2.4895 |
2.4528 | 0.13 | 100 | 2.4884 |
2.428 | 0.14 | 110 | 2.4872 |
2.4669 | 0.15 | 120 | 2.4858 |
2.4344 | 0.17 | 130 | 2.4842 |
2.4292 | 0.18 | 140 | 2.4825 |
2.4199 | 0.19 | 150 | 2.4807 |
2.3994 | 0.2 | 160 | 2.4790 |
2.394 | 0.22 | 170 | 2.4771 |
2.4564 | 0.23 | 180 | 2.4752 |
2.4278 | 0.24 | 190 | 2.4734 |
2.4446 | 0.26 | 200 | 2.4717 |
2.3944 | 0.27 | 210 | 2.4703 |
2.4077 | 0.28 | 220 | 2.4689 |
2.4165 | 0.29 | 230 | 2.4678 |
2.4031 | 0.31 | 240 | 2.4667 |
2.3953 | 0.32 | 250 | 2.4660 |
2.3856 | 0.33 | 260 | 2.4651 |
2.3674 | 0.35 | 270 | 2.4646 |
2.4261 | 0.36 | 280 | 2.4643 |
2.4006 | 0.37 | 290 | 2.4638 |
2.3949 | 0.38 | 300 | 2.4638 |
2.4207 | 0.4 | 310 | 2.4638 |
2.4057 | 0.41 | 320 | 2.4638 |
2.4168 | 0.42 | 330 | 2.4641 |
2.395 | 0.44 | 340 | 2.4644 |
2.4121 | 0.45 | 350 | 2.4649 |
2.4041 | 0.46 | 360 | 2.4655 |
2.3799 | 0.47 | 370 | 2.4662 |
2.4049 | 0.49 | 380 | 2.4669 |
2.3492 | 0.5 | 390 | 2.4676 |
2.4105 | 0.51 | 400 | 2.4681 |
2.3855 | 0.52 | 410 | 2.4688 |
2.4315 | 0.54 | 420 | 2.4694 |
2.4082 | 0.55 | 430 | 2.4703 |
2.4911 | 0.56 | 440 | 2.4708 |
2.4467 | 0.58 | 450 | 2.4716 |
2.4166 | 0.59 | 460 | 2.4721 |
2.4174 | 0.6 | 470 | 2.4727 |
2.392 | 0.61 | 480 | 2.4732 |
2.37 | 0.63 | 490 | 2.4737 |
2.3936 | 0.64 | 500 | 2.4742 |
2.3892 | 0.65 | 510 | 2.4747 |
2.4089 | 0.67 | 520 | 2.4750 |
2.4316 | 0.68 | 530 | 2.4753 |
2.4167 | 0.69 | 540 | 2.4757 |
2.3993 | 0.7 | 550 | 2.4758 |
2.4529 | 0.72 | 560 | 2.4761 |
2.4466 | 0.73 | 570 | 2.4763 |
2.3683 | 0.74 | 580 | 2.4766 |
2.4494 | 0.76 | 590 | 2.4768 |
2.4218 | 0.77 | 600 | 2.4769 |
2.4086 | 0.78 | 610 | 2.4773 |
2.4271 | 0.79 | 620 | 2.4774 |
2.4317 | 0.81 | 630 | 2.4776 |
2.4495 | 0.82 | 640 | 2.4777 |
2.4143 | 0.83 | 650 | 2.4779 |
2.3874 | 0.84 | 660 | 2.4780 |
2.4044 | 0.86 | 670 | 2.4781 |
2.3622 | 0.87 | 680 | 2.4781 |
2.3624 | 0.88 | 690 | 2.4784 |
2.3998 | 0.9 | 700 | 2.4783 |
2.3894 | 0.91 | 710 | 2.4784 |
2.4157 | 0.92 | 720 | 2.4785 |
2.4197 | 0.93 | 730 | 2.4785 |
2.3727 | 0.95 | 740 | 2.4786 |
2.3622 | 0.96 | 750 | 2.4786 |
2.3938 | 0.97 | 760 | 2.4787 |
2.404 | 0.99 | 770 | 2.4786 |
2.4571 | 1.0 | 780 | 2.4786 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.5.2
- Tokenizers 0.14.0