metadata
license: llama3
base_model: tsavage68/Summary_L3_1000steps_1e7rate_SFT2
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: Summary_L3_1000steps_1e6rate_03beta_CSFTDPO
results: []
Summary_L3_1000steps_1e6rate_03beta_CSFTDPO
This model is a fine-tuned version of tsavage68/Summary_L3_1000steps_1e7rate_SFT2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5961
- Rewards/chosen: 0.0294
- Rewards/rejected: -2.5656
- Rewards/accuracies: 0.1400
- Rewards/margins: 2.5950
- Logps/rejected: -23.8158
- Logps/chosen: -9.2849
- Logits/rejected: -1.1435
- Logits/chosen: -1.1436
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-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.5553 | 0.2004 | 50 | 0.5962 | 0.0778 | -1.2696 | 0.1400 | 1.3473 | -19.4956 | -9.1236 | -1.1038 | -1.1053 |
| 0.6585 | 0.4008 | 100 | 0.5962 | 0.0854 | -1.4439 | 0.1400 | 1.5292 | -20.0766 | -9.0982 | -1.1078 | -1.1092 |
| 0.6238 | 0.6012 | 150 | 0.5961 | 0.0687 | -2.1556 | 0.1400 | 2.2243 | -22.4490 | -9.1538 | -1.1298 | -1.1306 |
| 0.6065 | 0.8016 | 200 | 0.5961 | 0.0322 | -2.5726 | 0.1400 | 2.6048 | -23.8390 | -9.2754 | -1.1437 | -1.1438 |
| 0.6238 | 1.0020 | 250 | 0.5961 | 0.0294 | -2.5678 | 0.1400 | 2.5971 | -23.8230 | -9.2849 | -1.1438 | -1.1440 |
| 0.6238 | 1.2024 | 300 | 0.5961 | 0.0279 | -2.5674 | 0.1400 | 2.5953 | -23.8219 | -9.2899 | -1.1439 | -1.1440 |
| 0.6238 | 1.4028 | 350 | 0.5961 | 0.0304 | -2.5648 | 0.1400 | 2.5952 | -23.8131 | -9.2814 | -1.1438 | -1.1439 |
| 0.5718 | 1.6032 | 400 | 0.5961 | 0.0304 | -2.5648 | 0.1400 | 2.5952 | -23.8131 | -9.2814 | -1.1438 | -1.1439 |
| 0.5892 | 1.8036 | 450 | 0.5961 | 0.0338 | -2.5715 | 0.1400 | 2.6052 | -23.8353 | -9.2702 | -1.1435 | -1.1436 |
| 0.5718 | 2.0040 | 500 | 0.5961 | 0.0279 | -2.5720 | 0.1400 | 2.5999 | -23.8372 | -9.2897 | -1.1434 | -1.1435 |
| 0.5718 | 2.2044 | 550 | 0.5961 | 0.0266 | -2.5750 | 0.1400 | 2.6016 | -23.8472 | -9.2942 | -1.1438 | -1.1440 |
| 0.5545 | 2.4048 | 600 | 0.5961 | 0.0271 | -2.5761 | 0.1400 | 2.6032 | -23.8507 | -9.2925 | -1.1438 | -1.1440 |
| 0.5199 | 2.6052 | 650 | 0.5961 | 0.0271 | -2.5761 | 0.1400 | 2.6032 | -23.8507 | -9.2925 | -1.1438 | -1.1440 |
| 0.6238 | 2.8056 | 700 | 0.5961 | 0.0270 | -2.5764 | 0.1400 | 2.6035 | -23.8519 | -9.2928 | -1.1438 | -1.1440 |
| 0.6065 | 3.0060 | 750 | 0.5961 | 0.0315 | -2.5674 | 0.1400 | 2.5989 | -23.8216 | -9.2777 | -1.1434 | -1.1436 |
| 0.6412 | 3.2064 | 800 | 0.5961 | 0.0276 | -2.5662 | 0.1400 | 2.5937 | -23.8176 | -9.2909 | -1.1434 | -1.1436 |
| 0.6585 | 3.4068 | 850 | 0.5961 | 0.0277 | -2.5666 | 0.1400 | 2.5943 | -23.8191 | -9.2903 | -1.1434 | -1.1436 |
| 0.6238 | 3.6072 | 900 | 0.5961 | 0.0281 | -2.5670 | 0.1400 | 2.5952 | -23.8205 | -9.2891 | -1.1434 | -1.1436 |
| 0.5372 | 3.8076 | 950 | 0.5961 | 0.0310 | -2.5656 | 0.1400 | 2.5966 | -23.8159 | -9.2795 | -1.1435 | -1.1436 |
| 0.6238 | 4.0080 | 1000 | 0.5961 | 0.0294 | -2.5656 | 0.1400 | 2.5950 | -23.8158 | -9.2849 | -1.1435 | -1.1436 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.0.0+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1