--- license: apache-2.0 base_model: hZzy/qwen2.5-0.5b-sft-news-IFT tags: - alignment-handbook - ndcg - trl - expo - generated_from_trainer - trl - expo - generated_from_trainer datasets: - hZzy/train_pairwise model-index: - name: qwen2.5-0.5b-expo-L1EXPO-ES-0.1 results: [] --- [Visualize in Weights & Biases](https://wandb.ai/zhiyuzha-university-of-florida/huggingface/runs/f736bh29) # qwen2.5-0.5b-expo-L1EXPO-ES-0.1 This model is a fine-tuned version of [hZzy/qwen2.5-0.5b-sft-news-IFT](https://huggingface.co/hZzy/qwen2.5-0.5b-sft-news-IFT) on the hZzy/train_pairwise dataset. It achieves the following results on the evaluation set: - Loss: 0.5234 - Logps: -82.5192 - Logits: -0.4757 - Objective: 0.5225 - Dpo Loss: 0.7512 - Regularize: 0.5225 - Ranking Simple: 0.5254 - Ranking Idealized: 0.6030 - Ranking Idealized Expo: 0.5223 - Wo Beta: 14.0055 ## 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: 4 - eval_batch_size: 4 - seed: 42 - distributed_type: multi-GPU - num_devices: 3 - gradient_accumulation_steps: 12 - total_train_batch_size: 144 - total_eval_batch_size: 12 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Dpo Loss | Logits | Logps | Validation Loss | Objective | Ranking Idealized | Ranking Idealized Expo | Ranking Simple | Regularize | Wo Beta | |:-------------:|:------:|:----:|:--------:|:-------:|:--------:|:---------------:|:---------:|:-----------------:|:----------------------:|:--------------:|:----------:|:-------:| | 0.0448 | 0.1417 | 50 | 0.6936 | -1.4299 | -90.3888 | 0.0622 | 0.0621 | 0.6030 | 0.5223 | 0.5243 | 0.0621 | 16.0768 | | 0.1716 | 0.2834 | 100 | 0.6982 | -1.3597 | -88.7675 | 0.1556 | 0.1559 | 0.6030 | 0.5223 | 0.5274 | 0.1559 | 15.9436 | | 0.2858 | 0.4251 | 150 | 0.7183 | -1.2546 | -79.5067 | 0.2912 | 0.2923 | 0.6030 | 0.5223 | 0.5228 | 0.2923 | 15.0570 | | 0.3544 | 0.5668 | 200 | 0.7309 | -0.8432 | -83.8485 | 0.3898 | 0.3890 | 0.6030 | 0.5223 | 0.5228 | 0.3890 | 14.7122 | | 0.375 | 0.7085 | 250 | 0.7353 | -0.6734 | -81.2900 | 0.4398 | 0.4375 | 0.6030 | 0.5223 | 0.5243 | 0.4375 | 14.4729 | | 0.3592 | 0.8503 | 300 | 0.7348 | -0.5501 | -84.4144 | 0.4422 | 0.4388 | 0.6030 | 0.5223 | 0.5233 | 0.4388 | 14.4403 | | 0.3351 | 0.9920 | 350 | 0.7354 | -0.5360 | -82.9375 | 0.4676 | 0.4602 | 0.6030 | 0.5223 | 0.5342 | 0.4602 | 14.2722 | | 0.3056 | 1.1337 | 400 | 0.7470 | -0.5686 | -80.5606 | 0.4842 | 0.4804 | 0.6030 | 0.5223 | 0.5254 | 0.4804 | 14.2812 | | 0.2932 | 1.2754 | 450 | 0.7439 | -0.5565 | -83.6231 | 0.4805 | 0.4755 | 0.6030 | 0.5223 | 0.5280 | 0.4755 | 14.4640 | | 0.2864 | 1.4171 | 500 | 0.7510 | -0.6557 | -82.9178 | 0.4964 | 0.4971 | 0.6030 | 0.5223 | 0.5274 | 0.4971 | 14.2823 | | 0.2635 | 1.5588 | 550 | 0.7503 | -0.6184 | -81.1614 | 0.5023 | 0.5043 | 0.6030 | 0.5223 | 0.5228 | 0.5043 | 14.0632 | | 0.2561 | 1.7005 | 600 | 0.7487 | -0.5805 | -84.7039 | 0.4980 | 0.4964 | 0.6030 | 0.5223 | 0.5233 | 0.4964 | 14.3352 | | 0.2448 | 1.8422 | 650 | 0.7503 | -0.4274 | -83.4629 | 0.5171 | 0.5191 | 0.6030 | 0.5223 | 0.5233 | 0.5191 | 14.2153 | | 0.2235 | 1.9839 | 700 | 0.7483 | -0.5057 | -81.7196 | 0.4963 | 0.4949 | 0.6030 | 0.5223 | 0.5233 | 0.4949 | 14.2026 | | 0.21 | 2.1256 | 750 | 0.7512 | -0.4757 | -82.5192 | 0.5234 | 0.5225 | 0.6030 | 0.5223 | 0.5254 | 0.5225 | 14.0055 | | 0.1988 | 2.2674 | 800 | 0.7496 | -0.5578 | -81.0564 | 0.5140 | 0.5114 | 0.6030 | 0.5223 | 0.5295 | 0.5114 | 14.1030 | | 0.1845 | 2.4091 | 850 | 0.7516 | -0.5129 | -82.6326 | 0.5205 | 0.5186 | 0.6030 | 0.5223 | 0.5311 | 0.5186 | 14.1518 | | 0.1741 | 2.5508 | 900 | 0.7507 | -0.4790 | -82.9809 | 0.5132 | 0.5118 | 0.6030 | 0.5223 | 0.5238 | 0.5118 | 14.2459 | | 0.1659 | 2.6925 | 950 | 0.7500 | -0.4840 | -83.8330 | 0.5189 | 0.5193 | 0.6030 | 0.5223 | 0.5238 | 0.5193 | 14.3029 | | 0.1539 | 2.8342 | 1000 | 0.7499 | -0.4671 | -82.8831 | 0.5137 | 0.5127 | 0.6030 | 0.5223 | 0.5269 | 0.5127 | 14.1925 | | 0.1445 | 2.9806 | 1050 | 0.5116 | -83.1677| -0.5531 | 0.5112 | 0.7478 | 0.5112 | 0.5248 | 0.6030 | 0.5223 | 14.2141 | | 0.1261 | 3.1223 | 1100 | 0.5157 | -83.5954| -0.5488 | 0.5165 | 0.7515 | 0.5165 | 0.5233 | 0.6030 | 0.5223 | 14.1783 | | 0.1146 | 3.2641 | 1150 | 0.5175 | -83.4265| -0.5372 | 0.5161 | 0.7487 | 0.5161 | 0.5264 | 0.6030 | 0.5223 | 14.1956 | | 0.1076 | 3.4058 | 1200 | 0.5169 | -83.9912| -0.4946 | 0.5160 | 0.7492 | 0.5160 | 0.5274 | 0.6030 | 0.5223 | 14.1241 | | 0.0981 | 3.5475 | 1250 | 0.5175 | -83.3791| -0.5087 | 0.5185 | 0.7500 | 0.5185 | 0.5311 | 0.6030 | 0.5223 | 14.2158 | ### Framework versions - Transformers 4.42.0 - Pytorch 2.3.0+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1