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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: Qwen/Qwen2-7B
metrics:
- accuracy
- precision
- recall
model-index:
- name: QWEN_2_7B_MT
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# QWEN_2_7B_MT
This model is a fine-tuned version of [Qwen/Qwen2-7B](https://huggingface.co./Qwen/Qwen2-7B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7702
- Accuracy: 0.78
- Precision: 0.7979
- Recall: 0.75
- F1 score: 0.7732
## 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| 0.93 | 0.25 | 200 | 0.8818 | 0.6517 | 0.7264 | 0.4867 | 0.5828 |
| 0.6783 | 0.5 | 400 | 1.1545 | 0.59 | 0.7411 | 0.2767 | 0.4029 |
| 0.6849 | 0.75 | 600 | 0.7826 | 0.685 | 0.7424 | 0.5667 | 0.6427 |
| 0.6378 | 1.0 | 800 | 0.7399 | 0.695 | 0.7647 | 0.5633 | 0.6488 |
| 0.4773 | 1.25 | 1000 | 0.9978 | 0.66 | 0.8077 | 0.42 | 0.5526 |
| 0.4842 | 1.5 | 1200 | 0.6576 | 0.7333 | 0.6902 | 0.8467 | 0.7605 |
| 0.456 | 1.75 | 1400 | 0.6290 | 0.77 | 0.8068 | 0.71 | 0.7553 |
| 0.464 | 2.0 | 1600 | 0.6295 | 0.7617 | 0.7774 | 0.7333 | 0.7547 |
| 0.3689 | 2.25 | 1800 | 0.6090 | 0.7783 | 0.8224 | 0.71 | 0.7621 |
| 0.307 | 2.5 | 2000 | 0.6058 | 0.7733 | 0.7808 | 0.76 | 0.7703 |
| 0.3302 | 2.75 | 2200 | 0.6024 | 0.7867 | 0.7810 | 0.7967 | 0.7888 |
| 0.3156 | 3.0 | 2400 | 0.7082 | 0.765 | 0.8272 | 0.67 | 0.7403 |
| 0.2571 | 3.25 | 2600 | 0.9494 | 0.7017 | 0.8168 | 0.52 | 0.6354 |
| 0.2593 | 3.5 | 2800 | 0.6498 | 0.7717 | 0.8030 | 0.72 | 0.7592 |
| 0.2458 | 3.75 | 3000 | 0.6434 | 0.7867 | 0.7810 | 0.7967 | 0.7888 |
| 0.2135 | 4.0 | 3200 | 0.7042 | 0.775 | 0.7978 | 0.7367 | 0.7660 |
| 0.1582 | 4.25 | 3400 | 0.6730 | 0.78 | 0.7530 | 0.8333 | 0.7911 |
| 0.158 | 4.5 | 3600 | 0.7538 | 0.7783 | 0.8104 | 0.7267 | 0.7663 |
| 0.2043 | 4.75 | 3800 | 0.7398 | 0.785 | 0.8065 | 0.75 | 0.7772 |
| 0.163 | 5.0 | 4000 | 0.7702 | 0.78 | 0.7979 | 0.75 | 0.7732 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |