Edit model card

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
Downloads last month
1
Unable to determine this model’s pipeline type. Check the docs .

Adapter for

Dataset used to train EllieS/Temp-L1-SFT-L2-KTO