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simonycl_-_llama-3-8b-instruct-metamath-armorm-gguf
RichardErkhov/simonycl_-_llama-3-8b-instruct-metamath-armorm-gguf
simonycl_-_llama-3-8b-instruct-metamath-armorm-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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At a glance
- Access
- Public
- Created
- Sep 25, 2024
- Updated
- Sep 25, 2024
- SHA
- 3a03cd9c
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
llama-3-8b-instruct-metamath-armorm - GGUF
- Model creator: https://huggingface.co/simonycl/
- Original model: https://huggingface.co/simonycl/llama-3-8b-instruct-metamath-armorm/
Original model description:
library_name: transformers license: llama3 base_model: meta-llama/Meta-Llama-3-8B-Instruct tags:
- alignment-handbook
- generated_from_trainer datasets:
- simonycl/Meta-Llama-3-8B-Instruct-metamath-rm-annotate model-index:
- name: llama-3-8b-instruct-metamath-armorm results: []
<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
llama-3-8b-instruct-metamath-armorm
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the simonycl/Meta-Llama-3-8B-Instruct-metamath-rm-annotate dataset. It achieves the following results on the evaluation set:
- Loss: 0.1754
- Rewards/chosen: -4.0084
- Rewards/rejected: -10.7133
- Rewards/accuracies: 0.9260
- Rewards/margins: 6.7050
- Logps/rejected: -1190.5024
- Logps/chosen: -493.8166
- Logits/rejected: -0.1943
- Logits/chosen: -0.5449
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: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- total_eval_batch_size: 8
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.1771 | 0.7881 | 400 | 0.1754 | -4.0084 | -10.7133 | 0.9260 | 6.7050 | -1190.5024 | -493.8166 | -0.1943 | -0.5449 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Created
- Sep 25, 2024
- Updated
- Sep 25, 2024