qwen2.5-7b-dpo-list_mle
This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct-1M on the yangzhao02/ListUltraFeedback dataset. It achieves the following results on the evaluation set:
- Loss: 6.8770
- Logps: -731.7206
- Logits: -0.5560
- Rank Correct Batch: 16.5650
- Rank Pair Batch: 28.0
- Rank Accuracy Batch: 0.5916
Model description
More information needed
Intended uses & limitations
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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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 8
- 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 | Logps | Logits | Rank Correct Batch | Rank Pair Batch | Rank Accuracy Batch |
---|---|---|---|---|---|---|---|---|
7.253 | 0.2672 | 125 | 7.2435 | -631.0031 | -0.5630 | 16.0366 | 28.0 | 0.5727 |
7.0458 | 0.5344 | 250 | 6.9577 | -711.2150 | -0.5474 | 16.4350 | 28.0 | 0.5870 |
6.879 | 0.8016 | 375 | 6.8770 | -731.7206 | -0.5560 | 16.5650 | 28.0 | 0.5916 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.6.0+cu126
- Datasets 2.19.1
- Tokenizers 0.20.3
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