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mlfoundations-dev_-_llama3-1_8b_baseline_infinity_instruct-gguf
RichardErkhov/mlfoundations-dev_-_llama3-1_8b_baseline_infinity_instruct-gguf
mlfoundations-dev_-_llama3-1_8b_baseline_infinity_instruct-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
- May 8, 2025
- Updated
- May 8, 2025
- SHA
- 470fc621
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
llama3-1_8b_baseline_infinity_instruct - GGUF
- Model creator: https://huggingface.co/mlfoundations-dev/
- Original model: https://huggingface.co/mlfoundations-dev/llama3-1_8b_baseline_infinity_instruct/
Original model description:
library_name: transformers license: llama3.1 base_model: meta-llama/Meta-Llama-3.1-8B tags:
- llama-factory
- full
- generated_from_trainer model-index:
- name: llama3-1_8b_baseline_infinity_instruct 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. -->
llama3-1_8b_baseline_infinity_instruct
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B on the BAAI/Infinity-Instruct dataset. It achieves the following results on the evaluation set:
- Loss: 0.9010
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-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 32
- total_train_batch_size: 512
- total_eval_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.1
- lr_scheduler_warmup_steps: 1738
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9018 | 1.0 | 423 | 0.9103 |
| 0.8586 | 2.0 | 846 | 0.9001 |
| 0.8143 | 3.0 | 1269 | 0.9010 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
- Created
- May 8, 2025
- Updated
- May 8, 2025