llama-3.1-8b-instruct-armorm
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the simonycl/llama3.1-ultrafeedback-annotate-armorm dataset. It achieves the following results on the evaluation set:
- Loss: 0.3837
- Rewards/chosen: -3.2511
- Rewards/rejected: -5.1202
- Rewards/accuracies: 0.8644
- Rewards/margins: 1.8691
- Logps/rejected: -797.6878
- Logps/chosen: -602.0981
- Logits/rejected: -1.3603
- Logits/chosen: -1.3921
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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- total_eval_batch_size: 4
- 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 | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.4269 | 0.8444 | 400 | 0.3837 | -3.2511 | -5.1202 | 0.8644 | 1.8691 | -797.6878 | -602.0981 | -1.3603 | -1.3921 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for simonycl/llama-3.1-8b-instruct-ultrafeedback-armorm
Base model
meta-llama/Llama-3.1-8B
Finetuned
meta-llama/Llama-3.1-8B-Instruct