---
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: []
---

<!-- 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. -->

# llama2-7B_final_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: 0.5523
- 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