zephyr-7b-ipo-lora
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 18.3397
- Rewards/chosen: 0.0292
- Rewards/rejected: -0.1006
- Rewards/accuracies: 0.7200
- Rewards/margins: 0.1298
- Logps/rejected: -212.0379
- Logps/chosen: -255.2319
- Logits/rejected: -1.7967
- Logits/chosen: -2.0243
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 19.3937 | 1.0 | 242 | 19.3450 | 0.0291 | -0.0729 | 0.7040 | 0.1020 | -211.7608 | -255.2333 | -1.7962 | -2.0237 |
| 19.376 | 2.0 | 484 | 18.8198 | 0.0270 | -0.0949 | 0.7020 | 0.1218 | -211.9809 | -255.2546 | -1.7954 | -2.0232 |
| 18.4503 | 3.0 | 726 | 18.3397 | 0.0292 | -0.1006 | 0.7200 | 0.1298 | -212.0379 | -255.2319 | -1.7967 | -2.0243 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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Model tree for sambar/zephyr-7b-ipo-lora
Base model
mistralai/Mistral-7B-v0.1