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---
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_weighted
model-index:
- name: qwen2.5-0.5b-expo-DPO-L2EXPO-noES2-0.1
results: []
---
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/zhiyuzha-university-of-florida/huggingface/runs/x320k7u5)
# qwen2.5-0.5b-expo-DPO-L2EXPO-noES2-0.1
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_weighted dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7416
- Logps: -92.3352
- Logits: -1.2949
- Objective: 0.7355
- Dpo Loss: 0.6749
- Ranking Simple: 0.5502
## 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Logps | Logits | Objective | Dpo Loss | Ranking Simple |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:--------------:|
| 0.6826 | 0.1417 | 50 | 0.7254 | -92.3092 | -1.5368 | 0.7272 | 0.6828 | 0.5280 |
| 0.6518 | 0.2834 | 100 | 0.7251 | -99.4396 | -1.6149 | 0.7209 | 0.6727 | 0.5383 |
| 0.5964 | 0.4251 | 150 | 0.7330 | -90.2166 | -1.4409 | 0.7247 | 0.6714 | 0.5409 |
| 0.5794 | 0.5668 | 200 | 0.7543 | -90.8808 | -1.5459 | 0.7437 | 0.6858 | 0.5378 |
| 0.5802 | 0.7085 | 250 | 0.7559 | -86.8752 | -1.5326 | 0.7459 | 0.6874 | 0.5404 |
| 0.5473 | 0.8503 | 300 | 0.7457 | -92.3480 | -1.5370 | 0.7389 | 0.6780 | 0.5487 |
| 0.5104 | 0.9920 | 350 | 0.7516 | -88.1940 | -1.3364 | 0.7372 | 0.6766 | 0.5430 |
| 0.4425 | 1.1337 | 400 | 0.7568 | -88.7595 | -1.2226 | 0.7489 | 0.6866 | 0.5440 |
| 0.4544 | 1.2754 | 450 | 0.7455 | -90.0551 | -1.3089 | 0.7365 | 0.6750 | 0.5481 |
| 0.4624 | 1.4171 | 500 | 0.7470 | -89.6256 | -1.2445 | 0.7387 | 0.6782 | 0.5533 |
| 0.4391 | 1.5588 | 550 | 0.7385 | -91.9954 | -1.1983 | 0.7304 | 0.6695 | 0.5487 |
| 0.4285 | 1.7005 | 600 | 0.7408 | -91.4037 | -1.1181 | 0.7317 | 0.6726 | 0.5502 |
| 0.4553 | 1.8422 | 650 | 0.7426 | -90.4160 | -1.2725 | 0.7335 | 0.6740 | 0.5559 |
| 0.4307 | 1.9839 | 700 | 0.7404 | -91.7855 | -1.2351 | 0.7342 | 0.6735 | 0.5585 |
| 0.3755 | 2.1256 | 750 | 0.7430 | -93.2394 | -1.3013 | 0.7369 | 0.6762 | 0.5487 |
| 0.3794 | 2.2674 | 800 | 0.7400 | -93.3133 | -1.2647 | 0.7335 | 0.6726 | 0.5543 |
| 0.373 | 2.4091 | 850 | 0.7410 | -92.9388 | -1.2593 | 0.7354 | 0.6747 | 0.5523 |
| 0.388 | 2.5508 | 900 | 0.7418 | -92.8924 | -1.2939 | 0.7363 | 0.6757 | 0.5502 |
| 0.3866 | 2.6925 | 950 | 0.7418 | -92.3290 | -1.2937 | 0.7358 | 0.6752 | 0.5507 |
| 0.3828 | 2.8342 | 1000 | 0.7417 | -92.3260 | -1.2946 | 0.7356 | 0.6749 | 0.5502 |
| 0.3743 | 2.9759 | 1050 | 0.7416 | -92.3352 | -1.2949 | 0.7355 | 0.6749 | 0.5502 |
### Framework versions
- Transformers 4.42.0
- Pytorch 2.3.0+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1
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