zephyr-dpop-qlora-uf-oursuf6k-5e-7

This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the generation/UF6k dataset. It achieves the following results on the evaluation set:

• Loss: 0.6903
• Positive Losses: 0.0369
• Dpo Losses: 0.6851
• Rewards/chosen: 0.0601
• Rewards/rejected: 0.0433
• Rewards/accuracies: 0.6090
• Rewards/margins: 0.0168
• Rewards/margins Max: 0.0933
• Rewards/margins Min: -0.0510
• Rewards/margins Std: 0.0482
• Logps/rejected: -254.2451
• Logps/chosen: -278.5801
• Logits/rejected: -2.7575
• Logits/chosen: -2.7964

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-07
• train_batch_size: 4
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• total_eval_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	Positive Losses	Dpo Losses	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Rewards/margins Max	Rewards/margins Min	Rewards/margins Std	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.6918	0.15	100	0.6930	0.0047	0.6922	0.0135	0.0117	0.6000	0.0019	0.0130	-0.0081	0.0070	-257.4135	-283.2392	-2.7718	-2.8105
0.6867	0.29	200	0.6917	0.0124	0.6900	0.0299	0.0235	0.6100	0.0063	0.0373	-0.0214	0.0194	-256.2250	-281.6053	-2.7690	-2.8075
0.6825	0.44	300	0.6909	0.0225	0.6879	0.0441	0.0333	0.625	0.0108	0.0619	-0.0341	0.0319	-255.2539	-280.1855	-2.7634	-2.8021
0.6808	0.58	400	0.6905	0.0314	0.6861	0.0543	0.0397	0.6170	0.0147	0.0808	-0.0436	0.0415	-254.6122	-279.1606	-2.7608	-2.7994
0.6769	0.73	500	0.6902	0.0330	0.6855	0.0585	0.0426	0.6120	0.0160	0.0885	-0.0487	0.0458	-254.3216	-278.7400	-2.7587	-2.7975
0.67	0.88	600	0.6903	0.0373	0.6851	0.0599	0.0432	0.6160	0.0167	0.0930	-0.0511	0.0481	-254.2623	-278.6050	-2.7602	-2.7988

Framework versions

• PEFT 0.7.1
• Transformers 4.39.0.dev0
• Pytorch 2.1.2+cu121
• Datasets 2.14.6
• Tokenizers 0.15.2