UTI_L3_1000steps_1e5rate_03beta_CSFTDPO
This model is a fine-tuned version of tsavage68/UTI_L3_1000steps_1e5rate_SFT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0069
- Rewards/chosen: 2.2757
- Rewards/rejected: -15.6836
- Rewards/accuracies: 0.9900
- Rewards/margins: 17.9593
- Logps/rejected: -115.4733
- Logps/chosen: -24.8934
- Logits/rejected: -1.4719
- Logits/chosen: -1.4307
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: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.0 | 0.6667 | 50 | 0.0072 | 1.8402 | -13.3590 | 0.9900 | 15.1992 | -107.7247 | -26.3451 | -1.4305 | -1.3941 |
| 0.0173 | 1.3333 | 100 | 0.0071 | 1.8455 | -14.4051 | 0.9900 | 16.2506 | -111.2116 | -26.3273 | -1.4331 | -1.3960 |
| 0.0347 | 2.0 | 150 | 0.0069 | 2.3483 | -14.9050 | 0.9900 | 17.2533 | -112.8780 | -24.6513 | -1.4557 | -1.4154 |
| 0.0 | 2.6667 | 200 | 0.0069 | 2.3179 | -15.0160 | 0.9900 | 17.3339 | -113.2480 | -24.7526 | -1.4584 | -1.4180 |
| 0.0173 | 3.3333 | 250 | 0.0069 | 2.3120 | -15.0851 | 0.9900 | 17.3971 | -113.4783 | -24.7723 | -1.4616 | -1.4212 |
| 0.0347 | 4.0 | 300 | 0.0069 | 2.3109 | -15.1144 | 0.9900 | 17.4254 | -113.5761 | -24.7759 | -1.4624 | -1.4219 |
| 0.0173 | 4.6667 | 350 | 0.0069 | 2.3085 | -15.1859 | 0.9900 | 17.4944 | -113.8144 | -24.7841 | -1.4649 | -1.4242 |
| 0.0173 | 5.3333 | 400 | 0.0069 | 2.2984 | -15.2571 | 0.9900 | 17.5555 | -114.0517 | -24.8176 | -1.4668 | -1.4260 |
| 0.0173 | 6.0 | 450 | 0.0069 | 2.2945 | -15.3467 | 0.9900 | 17.6412 | -114.3504 | -24.8307 | -1.4680 | -1.4272 |
| 0.0347 | 6.6667 | 500 | 0.0069 | 2.2859 | -15.4295 | 0.9900 | 17.7154 | -114.6264 | -24.8593 | -1.4694 | -1.4284 |
| 0.0 | 7.3333 | 550 | 0.0069 | 2.2833 | -15.5057 | 0.9900 | 17.7890 | -114.8804 | -24.8681 | -1.4703 | -1.4293 |
| 0.0347 | 8.0 | 600 | 0.0069 | 2.2775 | -15.5762 | 0.9900 | 17.8538 | -115.1155 | -24.8872 | -1.4709 | -1.4298 |
| 0.0 | 8.6667 | 650 | 0.0069 | 2.2759 | -15.6206 | 0.9900 | 17.8965 | -115.2633 | -24.8928 | -1.4712 | -1.4301 |
| 0.0173 | 9.3333 | 700 | 0.0069 | 2.2757 | -15.6425 | 0.9900 | 17.9182 | -115.3363 | -24.8933 | -1.4714 | -1.4302 |
| 0.0 | 10.0 | 750 | 0.0069 | 2.2743 | -15.6650 | 0.9900 | 17.9392 | -115.4112 | -24.8982 | -1.4717 | -1.4305 |
| 0.0173 | 10.6667 | 800 | 0.0069 | 2.2739 | -15.6785 | 0.9900 | 17.9524 | -115.4563 | -24.8992 | -1.4719 | -1.4307 |
| 0.0 | 11.3333 | 850 | 0.0069 | 2.2703 | -15.6667 | 0.9900 | 17.9370 | -115.4169 | -24.9113 | -1.4717 | -1.4306 |
| 0.0 | 12.0 | 900 | 0.0069 | 2.2749 | -15.6771 | 0.9900 | 17.9520 | -115.4516 | -24.8959 | -1.4719 | -1.4307 |
| 0.0173 | 12.6667 | 950 | 0.0069 | 2.2732 | -15.6753 | 0.9900 | 17.9485 | -115.4458 | -24.9018 | -1.4719 | -1.4307 |
| 0.0 | 13.3333 | 1000 | 0.0069 | 2.2757 | -15.6836 | 0.9900 | 17.9593 | -115.4733 | -24.8934 | -1.4719 | -1.4307 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.0.0+cu117
- Datasets 2.19.2
- Tokenizers 0.19.1
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Model tree for tsavage68/UTI_L3_1000steps_1e5rate_03beta_CSFTDPO
Base model
meta-llama/Meta-Llama-3-8B-Instruct
Finetuned
tsavage68/UTI_L3_1000steps_1e5rate_SFT