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--- |
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library_name: transformers |
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license: llama3.1 |
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base_model: meta-llama/Meta-Llama-3.1-8B-Instruct |
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tags: |
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- alignment-handbook |
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- generated_from_trainer |
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datasets: |
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- simonycl/llama3.1-ultrafeedback-annotate-armorm |
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model-index: |
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- name: llama-3.1-8b-instruct-armorm |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# llama-3.1-8b-instruct-armorm |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co./meta-llama/Meta-Llama-3.1-8B-Instruct) on the simonycl/llama3.1-ultrafeedback-annotate-armorm dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5123 |
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- Rewards/chosen: -2.5095 |
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- Rewards/rejected: -3.2703 |
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- Rewards/accuracies: 0.7782 |
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- Rewards/margins: 0.7608 |
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- Logps/rejected: -600.9280 |
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- Logps/chosen: -513.8394 |
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- Logits/rejected: -2.6733 |
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- Logits/chosen: -2.7845 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-07 |
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- train_batch_size: 2 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 0.2606 | 0.7886 | 400 | 0.5123 | -2.5095 | -3.2703 | 0.7782 | 0.7608 | -600.9280 | -513.8394 | -2.6733 | -2.7845 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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