base_model: meta-llama/Llama-2-13b-hf
library_name: peft
license: llama2
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: llama2_13B_LORA_FOR_CLASSIFICATION
results: []
llama2_13B_LORA_FOR_CLASSIFICATION
This model is a fine-tuned version of meta-llama/Llama-2-13b-hf on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.5708
Balanced Accuracy: 0.7079
Accuracy: 0.7530
Micro F1: 0.7530
Macro F1: 0.6771
Weighted F1: 0.7669
Classification Report: precision recall f1-score support
0 0.89 0.79 0.83 857 1 0.44 0.63 0.52 232
accuracy 0.75 1089 macro avg 0.67 0.71 0.68 1089
weighted avg 0.79 0.75 0.77 1089
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: 24
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
Training Loss | Epoch | Step | Accuracy | Balanced Accuracy | Classification Report | Validation Loss | Macro F1 | Micro F1 | Weighted F1 |
---|---|---|---|---|---|---|---|---|---|
0.4853 | 2.0 | 522 | 0.7750 | 0.7297 | precision recall f1-score support |
0 0.90 0.81 0.85 857
1 0.48 0.65 0.55 232
accuracy 0.78 1089
macro avg 0.69 0.73 0.70 1089 weighted avg 0.81 0.78 0.79 1089 | 0.5482 | 0.7009 | 0.7750 | 0.7864 | | 0.4116 | 3.0 | 783 | 0.7668 | 0.7182 | precision recall f1-score support
0 0.89 0.80 0.84 857
1 0.47 0.63 0.54 232
accuracy 0.77 1089
macro avg 0.68 0.72 0.69 1089 weighted avg 0.80 0.77 0.78 1089 | 0.5497 | 0.6903 | 0.7668 | 0.7786 | | 0.3224 | 4.0 | 1044 | 0.5708 | 0.7079 | 0.7530 | 0.7530 | 0.6771 | 0.7669 | precision recall f1-score support
0 0.89 0.79 0.83 857
1 0.44 0.63 0.52 232
accuracy 0.75 1089
macro avg 0.67 0.71 0.68 1089 weighted avg 0.79 0.75 0.77 1089 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1