File size: 2,903 Bytes
c7f70d3 8a75540 c7f70d3 8a75540 c7f70d3 8a75540 c7f70d3 |
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 |
---
license: mit
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- jan-hq/distilabel_dpo_pairs_binarized
- argilla/OpenHermes2.5-dpo-binarized-alpha
- jan-hq/capybara_dpo_binarized
- jan-hq/bagel_dpo_binarized
- jan-hq/ultrafeedback_preferences_cleaned_binarized
- jan-hq/openmath_instruct_dpo_binarized
- jan-hq/distil_math_dpo_binarized
- jan-hq/evol_codealpaca_dpo_binarized
base_model: TomGrc/FusionNet_7Bx2_MoE_v0.1
model-index:
- name: stealth-finance-v2-dpo-adapter
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. -->
# stealth-finance-v2-dpo-adapter
This model is a fine-tuned version of [TomGrc/FusionNet_7Bx2_MoE_v0.1](https://huggingface.co/TomGrc/FusionNet_7Bx2_MoE_v0.1) on the jan-hq/distilabel_dpo_pairs_binarized, the argilla/OpenHermes2.5-dpo-binarized-alpha, the jan-hq/capybara_dpo_binarized, the jan-hq/bagel_dpo_binarized, the jan-hq/ultrafeedback_preferences_cleaned_binarized, the jan-hq/openmath_instruct_dpo_binarized, the jan-hq/distil_math_dpo_binarized and the jan-hq/evol_codealpaca_dpo_binarized datasets.
It achieves the following results on the evaluation set:
- Loss: 0.1290
- Rewards/chosen: -0.1799
- Rewards/rejected: -6.0696
- Rewards/accuracies: 0.8597
- Rewards/margins: 5.8897
- Logps/rejected: -324.0384
- Logps/chosen: -275.3572
- Logits/rejected: -0.7749
- Logits/chosen: -0.7773
## 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-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- total_eval_batch_size: 2
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.3593 | 1.0 | 3280 | 0.1290 | -0.1799 | -6.0696 | 0.8597 | 5.8897 | -324.0384 | -275.3572 | -0.7749 | -0.7773 |
### Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0 |