metadata
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: zephyr-7b-dpo-full
results: []
zephyr-7b-dpo-full
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: 0.5026
- Rewards/chosen: -1.0472
- Rewards/rejected: -1.9901
- Rewards/accuracies: 0.7619
- Rewards/margins: 0.9430
- Logps/rejected: -460.7913
- Logps/chosen: -388.8264
- Logits/rejected: 1.7625
- Logits/chosen: 1.0392
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: 615
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- 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 |
---|---|---|---|---|---|---|---|---|---|---|---|
0.5736 | 0.21 | 100 | 0.5842 | -0.3837 | -0.8468 | 0.7242 | 0.4632 | -346.4596 | -322.4754 | -2.3510 | -2.4330 |
0.5116 | 0.42 | 200 | 0.5308 | -0.9042 | -1.7331 | 0.7520 | 0.8289 | -435.0859 | -374.5288 | 0.5012 | 0.0459 |
0.5027 | 0.63 | 300 | 0.5084 | -0.8877 | -1.7467 | 0.7639 | 0.8590 | -436.4478 | -372.8834 | 1.8224 | 1.1385 |
0.4823 | 0.84 | 400 | 0.5037 | -1.1953 | -2.1521 | 0.7619 | 0.9568 | -476.9852 | -403.6375 | 1.9978 | 1.3075 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0