metadata
library_name: peft
tags:
- generated_from_trainer
datasets:
- patent-classification
metrics:
- accuracy
base_model: NousResearch/Llama-2-7b-hf
model-index:
- name: llama-2-7b-flash-attention2-lora-patent-classification
results: []
llama-2-7b-flash-attention2-lora-patent-classification
This model is a fine-tuned version of NousResearch/Llama-2-7b-hf on the patent-classification dataset. It achieves the following results on the evaluation set:
- Loss: 1.5598
- Accuracy: 0.436
- Precision Macro: 0.4276
- Recall Macro: 0.3658
- F1-score Macro: 0.3707
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: 0.0002
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Macro | Recall Macro | F1-score Macro |
|---|---|---|---|---|---|---|---|
| 1.4059 | 1.0 | 6250 | 1.9046 | 0.3748 | 0.3815 | 0.3173 | 0.3012 |
| 1.1153 | 2.0 | 12500 | 1.6457 | 0.419 | 0.4162 | 0.3461 | 0.3466 |
| 1.0234 | 3.0 | 18750 | 1.5598 | 0.436 | 0.4276 | 0.3658 | 0.3707 |
Framework versions
- PEFT 0.7.2.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0