llama-3-8b-instruct-simpo
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the princeton-nlp/llama3-ultrafeedback dataset. It achieves the following results on the evaluation set:
- Loss: 0.7528
- Original Losses: 2.0491
- Weight: 0.3713
- Abs Diff: 3.1759
- Rewards/chosen: -45.3959
- Rewards/rejected: -50.3664
- Rewards/accuracies: 0.6976
- Rewards/margins: 4.9705
- Logps/rejected: -20.1465
- Logps/chosen: -18.1584
- Logits/rejected: 1.8309
- Logits/chosen: 1.7177
- All Logps 1: -7614.6904
- All Logps 1 Values: -7614.6909
- All Logps 2: 414.8609
- All Logps 2 Values: 414.8609
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-06
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- 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 | Original Losses | Weight | Abs Diff | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | All Logps 1 | All Logps 1 Values | All Logps 2 | All Logps 2 Values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.7506 | 0.8549 | 400 | 0.7528 | 2.0491 | 0.3713 | 3.1759 | -45.3959 | -50.3664 | 0.6976 | 4.9705 | -20.1465 | -18.1584 | 1.8309 | 1.7177 | -7614.6904 | -7614.6909 | 414.8609 | 414.8609 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.2.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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