Llama3_AAID_mixed_train
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the AAID_mixed dataset. It achieves the following results on the evaluation set:
- Loss: 0.8485
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: 0.0003
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3.0
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.4516 | 0.2188 | 200 | 0.8485 |
0.3476 | 0.4375 | 400 | 0.9426 |
0.242 | 0.6563 | 600 | 1.1041 |
0.1079 | 0.8750 | 800 | 1.2782 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for Holmeister/Llama3_AAID_mixed_train
Base model
meta-llama/Meta-Llama-3-8B