metadata
license: llama3
library_name: peft
tags:
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B
metrics:
- accuracy
- precision
- recall
model-index:
- name: llama3-8B_less_data_for_fact_update
results: []
llama3-8B_less_data_for_fact_update
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7586
- Accuracy: 0.7733
- Precision: 0.8015
- Recall: 0.7267
- F1 score: 0.7622
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: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 score |
|---|---|---|---|---|---|---|---|
| 0.8492 | 0.5 | 200 | 0.8538 | 0.65 | 0.6923 | 0.54 | 0.6067 |
| 0.7574 | 1.0 | 400 | 0.6427 | 0.7267 | 0.8036 | 0.6 | 0.6870 |
| 0.5003 | 1.5 | 600 | 0.5917 | 0.73 | 0.7066 | 0.7867 | 0.7445 |
| 0.4629 | 2.0 | 800 | 0.6470 | 0.7567 | 0.8235 | 0.6533 | 0.7286 |
| 0.3114 | 2.5 | 1000 | 0.6980 | 0.6967 | 0.7438 | 0.6 | 0.6642 |
| 0.3031 | 3.0 | 1200 | 0.6128 | 0.7567 | 0.8130 | 0.6667 | 0.7326 |
| 0.1783 | 3.5 | 1400 | 0.7288 | 0.7667 | 0.8175 | 0.6867 | 0.7464 |
| 0.1737 | 4.0 | 1600 | 0.7242 | 0.7533 | 0.7969 | 0.68 | 0.7338 |
| 0.0924 | 4.5 | 1800 | 0.7214 | 0.7733 | 0.7808 | 0.76 | 0.7703 |
| 0.0669 | 5.0 | 2000 | 0.7586 | 0.7733 | 0.8015 | 0.7267 | 0.7622 |
Framework versions
- PEFT 0.11.1
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1