metadata
license: apache-2.0
base_model: NousResearch/Yarn-Mistral-7b-128k
tags:
- generated_from_trainer
model-index:
- name: unraveled-7b-dpo-lora
results: []
unraveled-7b-dpo-lora
This model is a fine-tuned version of NousResearch/Yarn-Mistral-7b-128k on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5895
- Rewards/chosen: 0.1439
- Rewards/rejected: -0.1833
- Rewards/accuracies: 0.6880
- Rewards/margins: 0.3272
- Logps/rejected: -221.8329
- Logps/chosen: -266.1414
- Logits/rejected: -1.9675
- Logits/chosen: -2.0859
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: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 32
- total_train_batch_size: 256
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6313 | 1.0 | 242 | 0.6318 | 0.1228 | -0.0304 | 0.6600 | 0.1532 | -220.3036 | -266.3521 | -1.9863 | -2.1062 |
| 0.6013 | 2.0 | 484 | 0.5983 | 0.1484 | -0.1334 | 0.6760 | 0.2819 | -221.3338 | -266.0959 | -1.9723 | -2.0914 |
| 0.5889 | 3.0 | 726 | 0.5895 | 0.1439 | -0.1833 | 0.6880 | 0.3272 | -221.8329 | -266.1414 | -1.9675 | -2.0859 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1