metadata
library_name: transformers
base_model: data/OpenELM-1_1B-SFT
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: OpenELM-1_1B-DPO-2
results: []
OpenELM-1_1B-DPO-2
This model is a fine-tuned version of data/OpenELM-1_1B-SFT on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.7793
- Rewards/chosen: -11.75
- Rewards/rejected: -13.6875
- Rewards/accuracies: 0.7227
- Rewards/margins: 1.9141
- Logps/rejected: -564.0
- Logps/chosen: -556.0
- Logits/rejected: -13.0625
- Logits/chosen: -13.3125
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: 8
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6791 | 1.0 | 1911 | 0.7098 | -10.8125 | -11.9375 | 0.6992 | 1.1328 | -528.0 | -536.0 | -12.5625 | -12.6875 |
| 0.0506 | 2.0 | 3822 | 0.7793 | -11.75 | -13.6875 | 0.7227 | 1.9141 | -564.0 | -556.0 | -13.0625 | -13.3125 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.3.0
- Datasets 2.21.0
- Tokenizers 0.19.1