BullingerLM
Collection
Models Finetuned to write footnotes for Bullinger Digital (https://www.bullinger-digital.ch/)
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16 items
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Updated
llama3.1_lora_pretrain_EA
This model is a fine-tuned version of unsloth/Meta-Llama-3.1-8B-bnb-4bit on the pretrain_EA dataset.
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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0
- mixed_precision_training: Native AMP
Training results
Framework versions
- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1
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Model tree for Boffl/BullingerLM-llama3.1-8B-pretrain-EA
Base model
meta-llama/Llama-3.1-8B
Quantized
unsloth/Meta-Llama-3.1-8B-bnb-4bit