File size: 3,406 Bytes
5d863b5 ae1ed4e 5d863b5 96607ee 5d863b5 96607ee ae1ed4e 96607ee 5d863b5 96607ee 5d863b5 96607ee 5d863b5 96607ee 5d863b5 ae1ed4e |
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 93 94 95 96 97 98 |
---
license: apache-2.0
library_name: transformers
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
base_model: Qwen/Qwen2.5-14B-Instruct
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: lambda-qwen2.5-14b-dpo-test
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. -->
# lambda-qwen2.5-14b-dpo-test
This model is a fine-tuned version of [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co./Qwen/Qwen2.5-14B-Instruct) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4919
- Rewards/chosen: -2.4745
- Rewards/rejected: -3.3729
- Rewards/accuracies: 0.7400
- Rewards/margins: 0.8984
- Logps/rejected: -832.0724
- Logps/chosen: -737.5234
- Logits/rejected: -1.2739
- Logits/chosen: -1.2560
## 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-07
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 16
- 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 | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5269 | 0.2094 | 100 | 0.5333 | -1.6756 | -2.3320 | 0.7000 | 0.6564 | -727.9815 | -657.6356 | -1.3952 | -1.3850 |
| 0.5086 | 0.4187 | 200 | 0.5044 | -2.0906 | -2.9287 | 0.7040 | 0.8381 | -787.6511 | -699.1298 | -1.2939 | -1.2773 |
| 0.4787 | 0.6281 | 300 | 0.4948 | -2.2927 | -3.1689 | 0.7320 | 0.8762 | -811.6696 | -719.3386 | -1.2846 | -1.2646 |
| 0.4825 | 0.8375 | 400 | 0.4924 | -2.4470 | -3.3410 | 0.7400 | 0.8939 | -828.8748 | -734.7765 | -1.2644 | -1.2477 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/details_tanliboy__lambda-qwen2.5-14b-dpo-test)
| Metric |Value|
|-------------------|----:|
|Avg. |33.52|
|IFEval (0-Shot) |82.31|
|BBH (3-Shot) |48.45|
|MATH Lvl 5 (4-Shot)| 0.00|
|GPQA (0-shot) |14.99|
|MuSR (0-shot) |12.59|
|MMLU-PRO (5-shot) |42.75|
|