metadata
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: r-zephyr-7b-beta-qlora
results: []
r-zephyr-7b-beta-qlora
The 'r' means replicate. This model is a model replicated by using https://github.com/huggingface/alignment-handbook.
This model is a fine-tuned version on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.5232
- Rewards/chosen: -0.9374
- Rewards/rejected: -1.7181
- Rewards/accuracies: 0.7734
- Rewards/margins: 0.7807
- Logps/rejected: -420.1122
- Logps/chosen: -341.2448
- Logits/rejected: 0.6190
- Logits/chosen: 0.6345
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: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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: 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.5917 | 0.21 | 100 | 0.5950 | -0.3904 | -0.7775 | 0.7109 | 0.3872 | -326.0618 | -286.5451 | -1.9790 | -1.9769 |
| 0.5281 | 0.42 | 200 | 0.5492 | -0.8657 | -1.6137 | 0.7617 | 0.7479 | -409.6739 | -334.0814 | -0.2289 | -0.2367 |
| 0.5321 | 0.63 | 300 | 0.5321 | -0.7444 | -1.4427 | 0.7734 | 0.6983 | -392.5731 | -321.9463 | 0.3829 | 0.3741 |
| 0.5149 | 0.84 | 400 | 0.5233 | -0.9570 | -1.7432 | 0.7617 | 0.7862 | -422.6298 | -343.2071 | 0.6479 | 0.6688 |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2