UTI2_L3_625steps_1e8rate_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: 0.6930
- Rewards/chosen: 0.0036
- Rewards/rejected: 0.0030
- Rewards/accuracies: 0.3100
- Rewards/margins: 0.0007
- Logps/rejected: -28.4747
- Logps/chosen: -19.0912
- Logits/rejected: -1.1523
- Logits/chosen: -1.1487
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-08
- 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: 625
Training results
Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
---|---|---|---|---|---|---|---|---|---|---|---|
0.6931 | 0.3333 | 25 | 0.6916 | 0.0014 | -0.0018 | 0.1500 | 0.0032 | -28.4908 | -19.0987 | -1.1522 | -1.1486 |
0.6959 | 0.6667 | 50 | 0.6934 | 0.0017 | 0.0019 | 0.2800 | -0.0002 | -28.4782 | -19.0975 | -1.1525 | -1.1489 |
0.6919 | 1.0 | 75 | 0.6912 | 0.0039 | -0.0004 | 0.3800 | 0.0042 | -28.4859 | -19.0904 | -1.1522 | -1.1487 |
0.7011 | 1.3333 | 100 | 0.6916 | 0.0013 | -0.0021 | 0.3500 | 0.0034 | -28.4917 | -19.0989 | -1.1523 | -1.1488 |
0.6915 | 1.6667 | 125 | 0.6917 | 0.0003 | -0.0029 | 0.3400 | 0.0032 | -28.4943 | -19.1023 | -1.1522 | -1.1486 |
0.6967 | 2.0 | 150 | 0.6932 | 0.0027 | 0.0025 | 0.3600 | 0.0002 | -28.4763 | -19.0943 | -1.1525 | -1.1489 |
0.6894 | 2.3333 | 175 | 0.6908 | 0.0010 | -0.0040 | 0.3700 | 0.0050 | -28.4980 | -19.1000 | -1.1522 | -1.1487 |
0.6915 | 2.6667 | 200 | 0.6905 | 0.0038 | -0.0018 | 0.3500 | 0.0056 | -28.4905 | -19.0906 | -1.1523 | -1.1487 |
0.6964 | 3.0 | 225 | 0.6887 | 0.0058 | -0.0034 | 0.4200 | 0.0093 | -28.4961 | -19.0839 | -1.1522 | -1.1487 |
0.6946 | 3.3333 | 250 | 0.6933 | -0.0054 | -0.0054 | 0.3400 | -0.0000 | -28.5026 | -19.1214 | -1.1524 | -1.1488 |
0.6965 | 3.6667 | 275 | 0.6900 | 0.0072 | 0.0005 | 0.3600 | 0.0067 | -28.4830 | -19.0794 | -1.1525 | -1.1489 |
0.6953 | 4.0 | 300 | 0.6898 | 0.0014 | -0.0056 | 0.3800 | 0.0070 | -28.5032 | -19.0985 | -1.1524 | -1.1488 |
0.6909 | 4.3333 | 325 | 0.6920 | 0.0006 | -0.0020 | 0.3700 | 0.0026 | -28.4913 | -19.1012 | -1.1524 | -1.1489 |
0.6923 | 4.6667 | 350 | 0.6938 | -0.0013 | -0.0003 | 0.3600 | -0.0010 | -28.4858 | -19.1076 | -1.1524 | -1.1488 |
0.6965 | 5.0 | 375 | 0.6895 | 0.0056 | -0.0019 | 0.3800 | 0.0076 | -28.4911 | -19.0845 | -1.1524 | -1.1488 |
0.6973 | 5.3333 | 400 | 0.6910 | 0.0030 | -0.0015 | 0.3700 | 0.0045 | -28.4898 | -19.0934 | -1.1524 | -1.1489 |
0.693 | 5.6667 | 425 | 0.6911 | -0.0000 | -0.0044 | 0.3700 | 0.0044 | -28.4993 | -19.1033 | -1.1522 | -1.1486 |
0.695 | 6.0 | 450 | 0.6935 | 0.0034 | 0.0037 | 0.3300 | -0.0003 | -28.4724 | -19.0921 | -1.1524 | -1.1488 |
0.6878 | 6.3333 | 475 | 0.6901 | 0.0045 | -0.0019 | 0.3600 | 0.0064 | -28.4909 | -19.0882 | -1.1523 | -1.1487 |
0.6889 | 6.6667 | 500 | 0.6924 | 0.0046 | 0.0027 | 0.3200 | 0.0019 | -28.4758 | -19.0881 | -1.1523 | -1.1487 |
0.6899 | 7.0 | 525 | 0.6930 | 0.0036 | 0.0030 | 0.3100 | 0.0007 | -28.4747 | -19.0912 | -1.1523 | -1.1487 |
0.6932 | 7.3333 | 550 | 0.6930 | 0.0036 | 0.0030 | 0.3100 | 0.0007 | -28.4747 | -19.0912 | -1.1523 | -1.1487 |
0.6929 | 7.6667 | 575 | 0.6930 | 0.0036 | 0.0030 | 0.3100 | 0.0007 | -28.4747 | -19.0912 | -1.1523 | -1.1487 |
0.6949 | 8.0 | 600 | 0.6930 | 0.0036 | 0.0030 | 0.3100 | 0.0007 | -28.4747 | -19.0912 | -1.1523 | -1.1487 |
0.6936 | 8.3333 | 625 | 0.6930 | 0.0036 | 0.0030 | 0.3100 | 0.0007 | -28.4747 | -19.0912 | -1.1523 | -1.1487 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.0.0+cu117
- Datasets 2.19.2
- Tokenizers 0.19.1
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