smollm2-17b-dpo-cai-v1
This model is a fine-tuned version of moodlep/smollm2-1.7b-instr-sft-cai on the HuggingFaceH4/ultrafeedback_binarized and the HuggingFaceH4/cai-conversation-harmless datasets. It achieves the following results on the evaluation set:
- Loss: 0.6931
- Rewards/chosen: 0.0000
- Rewards/rejected: -0.0001
- Rewards/accuracies: 0.4339
- Rewards/margins: 0.0002
- Logps/rejected: -228.5849
- Logps/chosen: -245.0489
- Logits/rejected: -1.4322
- Logits/chosen: -1.3905
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: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6933 | 0.3883 | 100 | 0.6930 | -0.0013 | -0.0015 | 0.4358 | 0.0002 | -228.7255 | -245.1841 | -1.6940 | -1.6433 |
| 0.6931 | 0.7767 | 200 | 0.6929 | -0.0007 | -0.0011 | 0.4487 | 0.0004 | -228.6854 | -245.1230 | -1.2768 | -1.2404 |
Framework versions
- PEFT 0.14.0
- Transformers 4.45.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.20.3
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