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dpo-selective-longerrun
wxzhang/dpo-selective-longerrun
dpo-selective-longerrun is a text generation model from wxzhang. Use it when you need the model to write or continue text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Generation
- Library
- transformers
- Model type
- mistral
- Access
- Public
- Created
- Apr 2, 2024
- Updated
- Apr 3, 2024
- SHA
- 59c7c4d7
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Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
dpo-selective-longerrun
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4916
- Rewards/chosen: -0.6959
- Rewards/rejected: -2.0431
- Rewards/accuracies: 0.7579
- Rewards/margins: 1.3472
- Logps/rejected: -312.5994
- Logps/chosen: -310.2374
- Logits/rejected: -2.3498
- Logits/chosen: -2.3901
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-07
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 1500
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6163 | 0.1 | 100 | 0.6145 | 0.0147 | -0.2611 | 0.7024 | 0.2758 | -276.9589 | -296.0254 | -2.3069 | -2.3542 |
| 0.5608 | 0.21 | 200 | 0.5507 | -0.0898 | -0.8075 | 0.7401 | 0.7176 | -287.8870 | -298.1169 | -2.3806 | -2.4286 |
| 0.4934 | 0.31 | 300 | 0.5225 | -0.1646 | -1.0392 | 0.7579 | 0.8746 | -292.5221 | -299.6117 | -2.3416 | -2.3850 |
| 0.4812 | 0.42 | 400 | 0.5148 | -0.2130 | -1.1798 | 0.7599 | 0.9668 | -295.3333 | -300.5795 | -2.3285 | -2.3697 |
| 0.5217 | 0.52 | 500 | 0.5094 | -0.1747 | -1.1571 | 0.7599 | 0.9824 | -294.8788 | -299.8136 | -2.3074 | -2.3432 |
| 0.5069 | 0.63 | 600 | 0.5037 | -0.0404 | -1.0494 | 0.7659 | 1.0090 | -292.7251 | -297.1272 | -2.2444 | -2.2854 |
| 0.4582 | 0.73 | 700 | 0.5003 | -0.6338 | -1.7232 | 0.7599 | 1.0894 | -306.2008 | -308.9958 | -2.2469 | -2.2897 |
| 0.457 | 0.84 | 800 | 0.4907 | -0.4901 | -1.6054 | 0.7639 | 1.1153 | -303.8464 | -306.1228 | -2.2928 | -2.3342 |
| 0.4723 | 0.94 | 900 | 0.4933 | -0.4418 | -1.5567 | 0.7659 | 1.1149 | -302.8719 | -305.1562 | -2.3355 | -2.3762 |
| 0.3094 | 1.05 | 1000 | 0.4922 | -0.8030 | -2.0474 | 0.7639 | 1.2444 | -312.6856 | -312.3804 | -2.3698 | -2.4094 |
| 0.2725 | 1.15 | 1100 | 0.4921 | -0.5635 | -1.8640 | 0.7460 | 1.3005 | -309.0183 | -307.5903 | -2.3382 | -2.3785 |
| 0.2932 | 1.26 | 1200 | 0.4924 | -0.6522 | -2.0030 | 0.7579 | 1.3509 | -311.7977 | -309.3632 | -2.3511 | -2.3915 |
| 0.275 | 1.36 | 1300 | 0.4916 | -0.6366 | -1.9750 | 0.7599 | 1.3383 | -311.2369 | -309.0526 | -2.3531 | -2.3934 |
| 0.2768 | 1.47 | 1400 | 0.4922 | -0.7011 | -2.0464 | 0.7579 | 1.3453 | -312.6646 | -310.3419 | -2.3505 | -2.3908 |
| 0.2863 | 1.57 | 1500 | 0.4916 | -0.6959 | -2.0431 | 0.7579 | 1.3472 | -312.5994 | -310.2374 | -2.3498 | -2.3901 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.0
- Task
- Text Generation
- Library
- transformers
- Type
- mistral
- Created
- Apr 2, 2024
- Updated
- Apr 3, 2024