metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: Qwen/Qwen2-7B
metrics:
- accuracy
- precision
- recall
model-index:
- name: llama2-7B_final_MT
results: []
llama2-7B_final_MT
This model is a fine-tuned version of Qwen/Qwen2-7B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5523
- Accuracy: 0.8117
- Precision: 0.7913
- Recall: 0.8467
- F1 score: 0.8180
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: 16
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|---|---|---|
| 0.8396 | 0.5 | 200 | 0.8733 | 0.645 | 0.6064 | 0.8267 | 0.6996 |
| 0.6541 | 1.0 | 400 | 0.6882 | 0.695 | 0.7127 | 0.6533 | 0.6817 |
| 0.4601 | 1.5 | 600 | 0.6691 | 0.7067 | 0.6505 | 0.8933 | 0.7528 |
| 0.4437 | 2.0 | 800 | 0.5010 | 0.7833 | 0.7690 | 0.81 | 0.7890 |
| 0.3406 | 2.5 | 1000 | 0.5010 | 0.7767 | 0.7823 | 0.7667 | 0.7744 |
| 0.2919 | 3.0 | 1200 | 0.4927 | 0.8117 | 0.8127 | 0.81 | 0.8114 |
| 0.2219 | 3.5 | 1400 | 0.4971 | 0.8217 | 0.8044 | 0.85 | 0.8266 |
| 0.2154 | 4.0 | 1600 | 0.6404 | 0.7633 | 0.7147 | 0.8767 | 0.7874 |
| 0.1381 | 4.5 | 1800 | 0.5391 | 0.815 | 0.8 | 0.84 | 0.8195 |
| 0.1531 | 5.0 | 2000 | 0.5523 | 0.8117 | 0.7913 | 0.8467 | 0.8180 |
Framework versions
- PEFT 0.11.1
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1