llama3instruct_-cpo-10-0_4-9e-7-1_best
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the yakazimir/llama3-ultrafeedback-armorm dataset. It achieves the following results on the evaluation set:
- Loss: 1.6745
- Rewards/chosen: -20.9433
- Rewards/rejected: -28.0136
- Rewards/accuracies: 0.8434
- Rewards/margins: 7.0703
- Logps/rejected: -2.8014
- Logps/chosen: -2.0943
- Logits/rejected: -1.2513
- Logits/chosen: -1.2961
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: 9e-07
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.6588 | 0.8743 | 400 | 1.6787 | -21.0507 | -28.1366 | 0.8373 | 7.0859 | -2.8137 | -2.1051 | -1.2389 | -1.2835 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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Model tree for yakazimir/llama3instruct_-cpo-10-0_4-9e-7-1_best
Base model
meta-llama/Meta-Llama-3-8B-Instruct