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stealth-finance-v2-dpo-adapter
jan-hq/stealth-finance-v2-dpo-adapter
stealth-finance-v2-dpo-adapter is a machine learning model from jan-hq. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- mit
- Model type
- mixtral
- Access
- Public
- Created
- Feb 20, 2024
- Updated
- Feb 24, 2024
- SHA
- 8a755408
Base models
Model card
From the Hugging Face model README
<!-- 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 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
- Library
- peft
- Type
- mixtral
- License
- mit
- Created
- Feb 20, 2024
- Updated
- Feb 24, 2024