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NicholasCorrado_-_zephyr-7b-uf-dpo-2e-4bits
RichardErkhov/NicholasCorrado_-_zephyr-7b-uf-dpo-2e-4bits
NicholasCorrado_-_zephyr-7b-uf-dpo-2e-4bits is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
zephyr-7b-uf-dpo-2e - bnb 4bits
- Model creator: https://huggingface.co/NicholasCorrado/
- Original model: https://huggingface.co/NicholasCorrado/zephyr-7b-uf-dpo-2e/
Original model description:
library_name: transformers license: apache-2.0 base_model: alignment-handbook/zephyr-7b-sft-full tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer datasets:
- HuggingFaceH4/ultrafeedback_binarized model-index:
- name: zephyr-7b-uf-dpo-2e 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. -->
zephyr-7b-uf-dpo-2e
This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.5017
- Rewards/chosen: -1.6430
- Rewards/rejected: -2.9109
- Rewards/accuracies: 0.7891
- Rewards/margins: 1.2679
- Logps/rejected: -553.7540
- Logps/chosen: -426.9287
- Logits/rejected: 2.3524
- Logits/chosen: 1.4100
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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.5424 | 0.5021 | 120 | 0.5378 | -0.5794 | -1.3437 | 0.7578 | 0.7642 | -397.0288 | -320.5744 | -0.5261 | -0.7461 |
| 0.4857 | 1.0042 | 240 | 0.5071 | -0.9384 | -1.8536 | 0.7695 | 0.9153 | -448.0264 | -356.4662 | 0.8934 | 0.1618 |
| 0.3605 | 1.5063 | 360 | 0.4996 | -1.5624 | -2.7607 | 0.7734 | 1.1983 | -538.7272 | -418.8674 | 2.1269 | 1.2559 |
Framework versions
- Transformers 4.44.1
- Pytorch 2.1.2+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Type
- mistral
- Created
- Apr 17, 2025
- Updated
- Apr 17, 2025