metadata
library_name: transformers
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- simonycl/llama3.1-ultrafeedback-annotate-armorm
model-index:
- name: llama-3.1-8b-instruct-armorm
results: []
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: 0.3984
- Rewards/chosen: -3.3263
- Rewards/rejected: -5.1260
- Rewards/accuracies: 0.8286
- Rewards/margins: 1.7997
- Logps/rejected: -786.4965
- Logps/chosen: -595.5199
- Logits/rejected: -2.6865
- Logits/chosen: -2.7593
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: 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.4222 | 0.8443 | 400 | 0.3984 | -3.3263 | -5.1260 | 0.8286 | 1.7997 | -786.4965 | -595.5199 | -2.6865 | -2.7593 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1