File size: 2,706 Bytes
510524c c90ab5f 510524c c90ab5f 510524c |
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 |
---
license: gemma
library_name: peft
tags:
- llama-factory
- lora
- trl
- dpo
- generated_from_trainer
base_model: google/gemma-7b-it
model-index:
- name: Gemma-7B-It-ORPO-SALT-HALF
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. -->
# Gemma-7B-It-ORPO-SALT-HALF
This model is a fine-tuned version of [google/gemma-7b-it](https://huggingface.co/google/gemma-7b-it) on the dpo_mix_en and the bct_non_cot_dpo_500 datasets.
It achieves the following results on the evaluation set:
- Loss: 1.3159
- Rewards/chosen: -0.1249
- Rewards/rejected: -0.1471
- Rewards/accuracies: 0.5619
- Rewards/margins: 0.0222
- Logps/rejected: -1.4709
- Logps/chosen: -1.2488
- Logits/rejected: 253.8645
- Logits/chosen: 253.5439
- Sft Loss: 1.2488
- Odds Ratio Loss: 0.6713
## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 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 | Sft Loss | Odds Ratio Loss |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:---------------:|
| 1.422 | 0.8467 | 500 | 1.3896 | -0.1322 | -0.1546 | 0.5752 | 0.0224 | -1.5459 | -1.3222 | 250.5634 | 250.2739 | 1.3222 | 0.6733 |
| 1.3103 | 1.6935 | 1000 | 1.3313 | -0.1264 | -0.1489 | 0.5695 | 0.0224 | -1.4886 | -1.2642 | 253.1350 | 252.8147 | 1.2642 | 0.6718 |
| 1.2057 | 2.5402 | 1500 | 1.3159 | -0.1249 | -0.1471 | 0.5619 | 0.0222 | -1.4709 | -1.2488 | 253.8645 | 253.5439 | 1.2488 | 0.6713 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1 |