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_unl_entropy
results: []
qwen_unl_entropy
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: 1.6475
- Rewards/chosen: -1.3030
- Rewards/rejected: -1.4992
- Rewards/accuracies: 0.5712
- Rewards/margins: 0.1962
- Logps/rejected: -1.4992
- Logps/chosen: -1.3030
- Logits/rejected: 0.0833
- Logits/chosen: 0.0165
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 | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.6549 | 0.2141 | 400 | 1.6939 | -1.3375 | -1.4631 | 0.5564 | 0.1256 | -1.4631 | -1.3375 | 0.3664 | 0.2799 |
| 1.6692 | 0.4282 | 800 | 1.6718 | -1.3151 | -1.4532 | 0.5579 | 0.1381 | -1.4532 | -1.3151 | 0.3708 | 0.2889 |
| 1.6206 | 0.6422 | 1200 | 1.6640 | -1.3083 | -1.4522 | 0.5564 | 0.1438 | -1.4522 | -1.3083 | 0.3523 | 0.2714 |
| 1.6566 | 0.8563 | 1600 | 1.6600 | -1.3096 | -1.4585 | 0.5593 | 0.1488 | -1.4585 | -1.3096 | 0.3578 | 0.2764 |
| 1.7104 | 1.0704 | 2000 | 1.6553 | -1.3006 | -1.4569 | 0.5660 | 0.1563 | -1.4569 | -1.3006 | 0.2528 | 0.1781 |
| 1.6123 | 1.2845 | 2400 | 1.6521 | -1.3029 | -1.4743 | 0.5668 | 0.1713 | -1.4743 | -1.3029 | 0.1650 | 0.0956 |
| 1.6688 | 1.4986 | 2800 | 1.6486 | -1.3000 | -1.4729 | 0.5690 | 0.1729 | -1.4729 | -1.3000 | 0.1751 | 0.1050 |
| 1.6012 | 1.7127 | 3200 | 1.6495 | -1.3009 | -1.4722 | 0.5668 | 0.1713 | -1.4722 | -1.3009 | 0.2139 | 0.1401 |
| 1.5646 | 1.9267 | 3600 | 1.6478 | -1.2987 | -1.4778 | 0.5705 | 0.1791 | -1.4778 | -1.2987 | 0.1771 | 0.1052 |
| 1.5351 | 2.1408 | 4000 | 1.6470 | -1.3020 | -1.4952 | 0.5712 | 0.1932 | -1.4952 | -1.3020 | 0.1238 | 0.0547 |
| 1.5307 | 2.3549 | 4400 | 1.6469 | -1.3054 | -1.5043 | 0.5712 | 0.1988 | -1.5043 | -1.3054 | 0.0587 | -0.0064 |
| 1.5433 | 2.5690 | 4800 | 1.6472 | -1.3037 | -1.5017 | 0.5727 | 0.1980 | -1.5017 | -1.3037 | 0.1609 | 0.0880 |
| 1.5671 | 2.7831 | 5200 | 1.6473 | -1.3030 | -1.4994 | 0.5720 | 0.1964 | -1.4994 | -1.3030 | 0.0927 | 0.0252 |
| 1.5482 | 2.9972 | 5600 | 1.6475 | -1.3030 | -1.4992 | 0.5712 | 0.1962 | -1.4992 | -1.3030 | 0.0833 | 0.0165 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1