metadata
library_name: transformers
license: apache-2.0
base_model: tsavage68/Na_M2_1000steps_1e7_SFT
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: Na_M2_1000steps_1e7rate_01beta_cSFTDPO
results: []
Na_M2_1000steps_1e7rate_01beta_cSFTDPO
This model is a fine-tuned version of tsavage68/Na_M2_1000steps_1e7_SFT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Rewards/chosen: 2.1377
- Rewards/rejected: -11.0023
- Rewards/accuracies: 1.0
- Rewards/margins: 13.1400
- Logps/rejected: -189.9462
- Logps/chosen: -26.7554
- Logits/rejected: -2.3910
- Logits/chosen: -2.4209
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-07
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.0514 | 0.2667 | 50 | 0.0095 | 1.0907 | -3.6125 | 1.0 | 4.7032 | -116.0486 | -37.2253 | -2.5048 | -2.5196 |
| 0.0 | 0.5333 | 100 | 0.0000 | 1.9516 | -8.2814 | 1.0 | 10.2330 | -162.7370 | -28.6162 | -2.4273 | -2.4516 |
| 0.0 | 0.8 | 150 | 0.0000 | 2.0205 | -8.9692 | 1.0 | 10.9897 | -169.6156 | -27.9274 | -2.4141 | -2.4403 |
| 0.0 | 1.0667 | 200 | 0.0000 | 2.0546 | -9.4358 | 1.0 | 11.4904 | -174.2812 | -27.5861 | -2.4057 | -2.4333 |
| 0.0 | 1.3333 | 250 | 0.0000 | 2.0861 | -9.8928 | 1.0 | 11.9789 | -178.8511 | -27.2716 | -2.4011 | -2.4294 |
| 0.0 | 1.6 | 300 | 0.0000 | 2.0968 | -10.1847 | 1.0 | 12.2815 | -181.7704 | -27.1646 | -2.3981 | -2.4268 |
| 0.0 | 1.8667 | 350 | 0.0000 | 2.1068 | -10.4154 | 1.0 | 12.5222 | -184.0774 | -27.0641 | -2.3951 | -2.4241 |
| 0.0 | 2.1333 | 400 | 0.0000 | 2.1173 | -10.5894 | 1.0 | 12.7067 | -185.8174 | -26.9596 | -2.3948 | -2.4241 |
| 0.0 | 2.4 | 450 | 0.0000 | 2.1209 | -10.7301 | 1.0 | 12.8510 | -187.2248 | -26.9235 | -2.3923 | -2.4219 |
| 0.0 | 2.6667 | 500 | 0.0000 | 2.1295 | -10.8281 | 1.0 | 12.9576 | -188.2044 | -26.8375 | -2.3924 | -2.4220 |
| 0.0 | 2.9333 | 550 | 0.0000 | 2.1355 | -10.9054 | 1.0 | 13.0409 | -188.9772 | -26.7771 | -2.3914 | -2.4212 |
| 0.0 | 3.2 | 600 | 0.0000 | 2.1356 | -10.9448 | 1.0 | 13.0805 | -189.3718 | -26.7761 | -2.3903 | -2.4200 |
| 0.0 | 3.4667 | 650 | 0.0000 | 2.1418 | -10.9896 | 1.0 | 13.1314 | -189.8192 | -26.7140 | -2.3895 | -2.4193 |
| 0.0 | 3.7333 | 700 | 0.0000 | 2.1378 | -11.0004 | 1.0 | 13.1382 | -189.9273 | -26.7544 | -2.3901 | -2.4200 |
| 0.0 | 4.0 | 750 | 0.0000 | 2.1390 | -11.0020 | 1.0 | 13.1409 | -189.9431 | -26.7428 | -2.3910 | -2.4208 |
| 0.0 | 4.2667 | 800 | 0.0000 | 2.1358 | -11.0021 | 1.0 | 13.1378 | -189.9439 | -26.7747 | -2.3902 | -2.4201 |
| 0.0 | 4.5333 | 850 | 0.0000 | 2.1380 | -11.0024 | 1.0 | 13.1404 | -189.9469 | -26.7523 | -2.3908 | -2.4207 |
| 0.0 | 4.8 | 900 | 0.0000 | 2.1377 | -11.0023 | 1.0 | 13.1400 | -189.9462 | -26.7554 | -2.3910 | -2.4209 |
| 0.0 | 5.0667 | 950 | 0.0000 | 2.1377 | -11.0023 | 1.0 | 13.1400 | -189.9462 | -26.7554 | -2.3910 | -2.4209 |
| 0.0 | 5.3333 | 1000 | 0.0000 | 2.1377 | -11.0023 | 1.0 | 13.1400 | -189.9462 | -26.7554 | -2.3910 | -2.4209 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1