llama3-L1-SFT-L2-KTO
This model is a fine-tuned version of EllieS/TempReason-L1-llama3 on the EllieS/Temp-L2-DPO dataset. It achieves the following results on the evaluation set:
- Loss: 0.2122
- Rewards/chosen: 0.3257
- Rewards/rejected: -9.5548
- Rewards/accuracies: 1.0
- Rewards/margins: 9.8805
- Logps/rejected: -1018.5145
- Logps/chosen: -12.0858
- Logits/rejected: 1.0988
- Logits/chosen: 0.1932
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: 5e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- total_eval_batch_size: 2
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.2129 | 0.4994 | 1000 | 0.2124 | 0.3252 | -9.3514 | 1.0 | 9.6766 | -998.1762 | -12.1315 | 1.1081 | 0.2036 |
| 0.2118 | 0.9989 | 2000 | 0.2122 | 0.3257 | -9.5548 | 1.0 | 9.8805 | -1018.5145 | -12.0858 | 1.0988 | 0.1932 |
Framework versions
- PEFT 0.7.1
- Transformers 4.40.2
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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Base model
meta-llama/Meta-Llama-3-8B