metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: mnoukhov/pythia410m-sft-tldr
model-index:
- name: pythia410m-dpo2-tldr
results: []
pythia410m-dpo2-tldr
This model is a fine-tuned version of mnoukhov/pythia410m-sft-tldr on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6073
- Rewards/chosen: -1.2728
- Rewards/rejected: -1.5670
- Rewards/accuracies: 0.6761
- Rewards/margins: 0.2942
- Logps/rejected: -91.1163
- Logps/chosen: -91.1163
- Logps/ref Rejected: -59.5615
- Logps/ref Chosen: -65.6594
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: 1e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logps/ref Rejected | Logps/ref Chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6681 | 0.1999 | 335 | 0.6376 | -0.2343 | -0.3789 | 0.6615 | 0.1446 | -70.3464 | -70.3464 | -59.5615 | -65.6594 |
| 0.6485 | 0.3999 | 670 | 0.6171 | -0.9421 | -1.1796 | 0.6678 | 0.2375 | -84.5023 | -84.5023 | -59.5615 | -65.6594 |
| 0.6362 | 0.5998 | 1005 | 0.6095 | -1.1035 | -1.3785 | 0.6743 | 0.2750 | -87.7290 | -87.7290 | -59.5615 | -65.6594 |
| 0.6342 | 0.7998 | 1340 | 0.6063 | -1.2460 | -1.5415 | 0.6768 | 0.2955 | -90.5797 | -90.5797 | -59.5615 | -65.6594 |
| 0.6299 | 0.9997 | 1675 | 0.6073 | -1.2728 | -1.5670 | 0.6761 | 0.2942 | -91.1163 | -91.1163 | -59.5615 | -65.6594 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1