File size: 4,742 Bytes
8f1c473 fd365ca 8f1c473 fd365ca 8f1c473 fd365ca 8f1c473 5bba43b 8f1c473 5bba43b 8f1c473 5bba43b 8f1c473 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 |
---
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_ce_entropy
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# qwen_ce_entropy
This model is a fine-tuned version of [trl-lib/qwen1.5-0.5b-sft](https://huggingface.co/trl-lib/qwen1.5-0.5b-sft) on the yakazimir/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2625
- Rewards/chosen: -1.2622
- Rewards/rejected: -1.3864
- Rewards/accuracies: 0.5475
- Rewards/margins: 0.1242
- Logps/rejected: -1.3864
- Logps/chosen: -1.2622
- Logits/rejected: 0.1431
- Logits/chosen: 0.0760
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 1.2903 | 0.2141 | 400 | 1.3234 | -1.3231 | -1.4418 | 0.5556 | 0.1187 | -1.4418 | -1.3231 | 0.3478 | 0.2657 |
| 1.2586 | 0.4282 | 800 | 1.2926 | -1.2924 | -1.4167 | 0.5482 | 0.1243 | -1.4167 | -1.2924 | 0.3140 | 0.2391 |
| 1.217 | 0.6422 | 1200 | 1.2836 | -1.2833 | -1.4047 | 0.5475 | 0.1213 | -1.4047 | -1.2833 | 0.2906 | 0.2178 |
| 1.299 | 0.8563 | 1600 | 1.2774 | -1.2772 | -1.3985 | 0.5467 | 0.1213 | -1.3985 | -1.2772 | 0.2371 | 0.1683 |
| 1.2617 | 1.0704 | 2000 | 1.2726 | -1.2724 | -1.3958 | 0.5482 | 0.1234 | -1.3958 | -1.2724 | 0.1842 | 0.1180 |
| 1.1894 | 1.2845 | 2400 | 1.2689 | -1.2687 | -1.3924 | 0.5460 | 0.1238 | -1.3924 | -1.2687 | 0.1212 | 0.0586 |
| 1.2779 | 1.4986 | 2800 | 1.2662 | -1.2659 | -1.3880 | 0.5453 | 0.1221 | -1.3880 | -1.2659 | 0.1199 | 0.0573 |
| 1.225 | 1.7127 | 3200 | 1.2650 | -1.2647 | -1.3872 | 0.5490 | 0.1225 | -1.3872 | -1.2647 | 0.1854 | 0.1171 |
| 1.1621 | 1.9267 | 3600 | 1.2636 | -1.2634 | -1.3853 | 0.5475 | 0.1219 | -1.3853 | -1.2634 | 0.1551 | 0.0880 |
| 1.1565 | 2.1408 | 4000 | 1.2633 | -1.2631 | -1.3880 | 0.5482 | 0.1250 | -1.3880 | -1.2631 | 0.0952 | 0.0325 |
| 1.1515 | 2.3549 | 4400 | 1.2629 | -1.2626 | -1.3868 | 0.5467 | 0.1242 | -1.3868 | -1.2626 | 0.0880 | 0.0251 |
| 1.1364 | 2.5690 | 4800 | 1.2625 | -1.2623 | -1.3865 | 0.5467 | 0.1242 | -1.3865 | -1.2623 | 0.1292 | 0.0630 |
| 1.1256 | 2.7831 | 5200 | 1.2626 | -1.2623 | -1.3864 | 0.5475 | 0.1241 | -1.3864 | -1.2623 | 0.1208 | 0.0553 |
| 1.1655 | 2.9972 | 5600 | 1.2625 | -1.2622 | -1.3864 | 0.5475 | 0.1242 | -1.3864 | -1.2622 | 0.1431 | 0.0760 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
|