LLAMA3.1_ISCO_Classification
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0584
- Balanced Accuracy: 0.7218
- Accuracy: 0.7384
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss | Balanced Accuracy | Accuracy |
---|---|---|---|---|---|
0.1012 | 1.0 | 2641 | 1.0584 | 0.7218 | 0.7384 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for chilz/LLAMA3.1_ISCO_Classification
Base model
meta-llama/Llama-3.1-8B