metadata
library_name: transformers
license: other
base_model: trl-lib/qwen1.5-0.5b-sft
tags:
- alignment-handbook
- trl
- simpo
- generated_from_trainer
- trl
- simpo
- generated_from_trainer
datasets:
- yakazimir/ultrafeedback_binarized
model-index:
- name: qwen_cpo_entropy_0_1
results: []
qwen_cpo_entropy_0_1
This model is a fine-tuned version of trl-lib/qwen1.5-0.5b-sft on the yakazimir/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.7405
- Sft Loss: 1.6848
- Rewards/chosen: -1.7146
- Rewards/rejected: -2.3727
- Rewards/accuracies: 0.6773
- Rewards/margins: 0.6581
- Logps/rejected: -2.3727
- Logps/chosen: -1.7146
- Logits/rejected: 0.3000
- Logits/chosen: 0.1875
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: 1e-06
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Sft Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.8248 | 0.2141 | 400 | 0.8255 | 1.3905 | -1.3850 | -1.5360 | 0.5645 | 0.1510 | -1.5360 | -1.3850 | 0.3069 | 0.2210 |
| 0.7884 | 0.4282 | 800 | 0.7811 | 1.4857 | -1.5199 | -1.8625 | 0.6113 | 0.3426 | -1.8625 | -1.5199 | 0.4914 | 0.3895 |
| 0.8073 | 0.6422 | 1200 | 0.7653 | 1.5452 | -1.5531 | -1.9756 | 0.6298 | 0.4226 | -1.9756 | -1.5531 | 0.5229 | 0.4111 |
| 0.7417 | 0.8563 | 1600 | 0.7599 | 1.5652 | -1.5632 | -1.9862 | 0.6484 | 0.4230 | -1.9862 | -1.5632 | 0.5072 | 0.3924 |
| 0.8212 | 1.0704 | 2000 | 0.7518 | 1.5561 | -1.5506 | -2.0302 | 0.6543 | 0.4796 | -2.0302 | -1.5506 | 0.4351 | 0.3208 |
| 0.7326 | 1.2845 | 2400 | 0.7455 | 1.6027 | -1.6077 | -2.1582 | 0.6632 | 0.5505 | -2.1582 | -1.6077 | 0.4993 | 0.3799 |
| 0.7742 | 1.4986 | 2800 | 0.7444 | 1.6196 | -1.6148 | -2.1590 | 0.6632 | 0.5442 | -2.1590 | -1.6148 | 0.4611 | 0.3432 |
| 0.7597 | 1.7127 | 3200 | 0.7438 | 1.6039 | -1.6049 | -2.1441 | 0.6632 | 0.5392 | -2.1441 | -1.6049 | 0.3926 | 0.2796 |
| 0.7128 | 1.9267 | 3600 | 0.7399 | 1.6368 | -1.6446 | -2.2337 | 0.6780 | 0.5891 | -2.2337 | -1.6446 | 0.3607 | 0.2486 |
| 0.6636 | 2.1408 | 4000 | 0.7399 | 1.6738 | -1.6828 | -2.3162 | 0.6780 | 0.6334 | -2.3162 | -1.6828 | 0.3064 | 0.1955 |
| 0.6929 | 2.3549 | 4400 | 0.7421 | 1.7043 | -1.7385 | -2.4029 | 0.6795 | 0.6644 | -2.4029 | -1.7385 | 0.3030 | 0.1902 |
| 0.6939 | 2.5690 | 4800 | 0.7411 | 1.6769 | -1.7078 | -2.3536 | 0.6758 | 0.6458 | -2.3536 | -1.7078 | 0.1986 | 0.0944 |
| 0.6831 | 2.7831 | 5200 | 0.7409 | 1.6830 | -1.7130 | -2.3694 | 0.6766 | 0.6564 | -2.3694 | -1.7130 | 0.3256 | 0.2110 |
| 0.6951 | 2.9972 | 5600 | 0.7405 | 1.6848 | -1.7146 | -2.3727 | 0.6773 | 0.6581 | -2.3727 | -1.7146 | 0.3000 | 0.1875 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1