400STEPS_05beta_1e7rate_Meditron7B
This model is a fine-tuned version of epfl-llm/meditron-7b on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6864
- Rewards/chosen: 0.0004
- Rewards/rejected: -0.0144
- Rewards/accuracies: 0.4945
- Rewards/margins: 0.0148
- Logps/rejected: -27.8226
- Logps/chosen: -26.4806
- Logits/rejected: -0.6110
- Logits/chosen: -0.6109
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: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 400
Training results
Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
---|---|---|---|---|---|---|---|---|---|---|---|
0.6941 | 0.1 | 50 | 0.6931 | -0.0003 | -0.0011 | 0.4044 | 0.0008 | -27.7959 | -26.4820 | -0.6106 | -0.6104 |
0.6927 | 0.2 | 100 | 0.6912 | -0.0047 | -0.0093 | 0.4769 | 0.0046 | -27.8123 | -26.4908 | -0.6105 | -0.6104 |
0.6838 | 0.29 | 150 | 0.6896 | -0.0023 | -0.0105 | 0.5077 | 0.0082 | -27.8146 | -26.4860 | -0.6101 | -0.6100 |
0.6906 | 0.39 | 200 | 0.6886 | -0.0007 | -0.0107 | 0.4989 | 0.0100 | -27.8151 | -26.4828 | -0.6109 | -0.6108 |
0.6789 | 0.49 | 250 | 0.6877 | -0.0035 | -0.0154 | 0.5121 | 0.0119 | -27.8245 | -26.4884 | -0.6111 | -0.6110 |
0.6853 | 0.59 | 300 | 0.6852 | 0.0012 | -0.0160 | 0.5297 | 0.0172 | -27.8257 | -26.4791 | -0.6112 | -0.6111 |
0.6805 | 0.68 | 350 | 0.6877 | -0.0039 | -0.0162 | 0.4725 | 0.0122 | -27.8260 | -26.4893 | -0.6112 | -0.6110 |
0.6936 | 0.78 | 400 | 0.6864 | 0.0004 | -0.0144 | 0.4945 | 0.0148 | -27.8226 | -26.4806 | -0.6110 | -0.6109 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.0.0+cu117
- Datasets 2.17.0
- Tokenizers 0.15.1
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