zephyr-7b-spin-iter0-v0

This model is a fine-tuned model with SPIN starting with alignment-handbook/zephyr-7b-sft-full on the argilla/10k_prompts_SPIN_iter0_zephyr_top dataset.

It achieves the following results on the evaluation set:

• Loss: 0.2359
• Rewards/real: 1.3255
• Rewards/generated: -0.8966
• Rewards/accuracies: 0.9792
• Rewards/margins: 2.2221
• Logps/generated: -309.8145
• Logps/real: -304.9670
• Logits/generated: -2.7558
• Logits/real: -2.7547

MT-Bench results

Model	1st Turn Score	2nd Turn Score	Average Score
zephyr-7b-sft-full	6.6625	6.0250	6.34375
zephyr-7b-spin-iter0-v0	6.64375	6.1750	6.409375
zephyr-7b-spin-iter1-v0	6.90625	6.3000	6.603125
zephyr-7b-spin-iter2-v0	7.1375	6.3125	6.725000
zephyr-7b-spin-iter3-v0	7.09375	6.4500	6.771875

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

SPIN

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-07
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• total_eval_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 2.0

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/real	Rewards/generated	Rewards/accuracies	Rewards/margins	Logps/generated	Logps/real	Logits/generated	Logits/real
0.3011	0.96	25	0.2442	1.1606	-0.9851	0.9792	2.1457	-310.6989	-306.6157	-2.7644	-2.7641
0.0376	1.92	50	0.2359	1.3255	-0.8966	0.9792	2.2221	-309.8145	-304.9670	-2.7558	-2.7547

Framework versions

• Transformers 4.37.0
• Pytorch 2.1.2+cu121
• Datasets 2.14.6
• Tokenizers 0.15.2