File size: 2,759 Bytes
20bd7ae f5461fe 20bd7ae f5461fe 20bd7ae f5461fe 20bd7ae |
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 |
---
license: other
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B
datasets:
- EllieS/Temp-L2-DPO
model-index:
- name: llama3-L1-SFT-L2-DPO
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. -->
# llama3-L1-SFT-L2-DPO
This model is a fine-tuned version of [EllieS/TempReason-L1-llama3](https://huggingface.co/EllieS/TempReason-L1-llama3) on the EllieS/Temp-L2-DPO dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0028
- Rewards/chosen: -0.4016
- Rewards/rejected: -9.3312
- Rewards/accuracies: 1.0
- Rewards/margins: 8.9296
- Logps/rejected: -994.2072
- Logps/chosen: -84.5141
- Logits/rejected: 1.5698
- Logits/chosen: 0.6541
## 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-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0033 | 0.2497 | 1000 | 0.0065 | -0.3610 | -7.6953 | 1.0 | 7.3344 | -830.6234 | -80.4518 | 1.5489 | 0.7452 |
| 0.0013 | 0.4995 | 2000 | 0.0031 | -0.3798 | -9.1892 | 1.0 | 8.8094 | -980.0131 | -82.3365 | 1.5546 | 0.6455 |
| 0.0019 | 0.7492 | 3000 | 0.0028 | -0.3966 | -9.3440 | 1.0 | 8.9474 | -995.4902 | -84.0208 | 1.5703 | 0.6568 |
| 0.0011 | 0.9989 | 4000 | 0.0028 | -0.4016 | -9.3312 | 1.0 | 8.9296 | -994.2072 | -84.5141 | 1.5698 | 0.6541 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.40.2
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1 |