Llama3_AAID_mixed_train_deneme
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: 0.8216
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 |
---|---|---|---|
0.7577 | 0.0219 | 20 | 0.8374 |
0.4704 | 0.0438 | 40 | 0.8379 |
0.4495 | 0.0656 | 60 | 0.8216 |
0.4326 | 0.0875 | 80 | 0.8272 |
0.421 | 0.1094 | 100 | 0.8494 |
0.406 | 0.1313 | 120 | 0.8483 |
0.3974 | 0.1531 | 140 | 0.8315 |
0.3989 | 0.1750 | 160 | 0.8574 |
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_deneme
Base model
meta-llama/Meta-Llama-3-8B