Temp-L1-SFT-L2-KTO
This model is a fine-tuned version of EllieS/TempReason-L1 on the EllieS/Temp-L2-DPO dataset. It achieves the following results on the evaluation set:
- Loss: 0.2213
- Rewards/chosen: 0.2579
- Rewards/rejected: -6.0725
- Rewards/accuracies: 1.0
- Rewards/margins: 6.3304
- Logps/rejected: -652.1185
- Logps/chosen: -0.1197
- Logits/rejected: -2.6590
- Logits/chosen: -2.5711
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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- 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_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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.2255 | 0.2497 | 1000 | 0.2230 | 0.2551 | -5.4032 | 1.0 | 5.6583 | -585.1871 | -0.3988 | -2.6372 | -2.5514 |
| 0.2252 | 0.4994 | 2000 | 0.2215 | 0.2576 | -5.9860 | 1.0 | 6.2436 | -643.4705 | -0.1526 | -2.6560 | -2.5690 |
| 0.2264 | 0.7492 | 3000 | 0.2213 | 0.2579 | -6.0565 | 1.0 | 6.3144 | -650.5204 | -0.1267 | -2.6590 | -2.5715 |
| 0.2262 | 0.9989 | 4000 | 0.2213 | 0.2579 | -6.0725 | 1.0 | 6.3304 | -652.1185 | -0.1197 | -2.6590 | -2.5711 |
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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