---
base_model: Qwen/Qwen2-7B
library_name: peft
license: apache-2.0
metrics:
- accuracy
- precision
- recall
tags:
- generated_from_trainer
model-index:
- name: Qwen2_7B_Task2_semantic_pred
  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. -->

# Qwen2_7B_Task2_semantic_pred

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: 0.5963
- Accuracy: 0.8123
- Precision: 0.8123
- Recall: 0.8123
- F1 score: 0.8123

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| 0.6405        | 0.5208 | 200  | 0.5790          | 0.7666   | 0.7666    | 0.7666 | 0.7666   |
| 0.4689        | 1.0417 | 400  | 0.9852          | 0.6649   | 0.6649    | 0.6649 | 0.6649   |
| 0.3635        | 1.5625 | 600  | 0.4249          | 0.8188   | 0.8188    | 0.8188 | 0.8188   |
| 0.3197        | 2.0833 | 800  | 0.7777          | 0.7353   | 0.7353    | 0.7353 | 0.7353   |
| 0.267         | 2.6042 | 1000 | 0.7223          | 0.7679   | 0.7679    | 0.7679 | 0.7679   |
| 0.2272        | 3.125  | 1200 | 0.4841          | 0.8201   | 0.8201    | 0.8201 | 0.8201   |
| 0.1848        | 3.6458 | 1400 | 0.4985          | 0.8227   | 0.8227    | 0.8227 | 0.8227   |
| 0.1744        | 4.1667 | 1600 | 0.6254          | 0.8044   | 0.8044    | 0.8044 | 0.8044   |
| 0.1402        | 4.6875 | 1800 | 0.5963          | 0.8123   | 0.8123    | 0.8123 | 0.8123   |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.3.0
- Datasets 2.20.0
- Tokenizers 0.19.1