---
license: other
base_model: Qwen/Qwen1.5-1.8B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Qwen1.5_1.8B_ledgar
  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. -->

# Qwen1.5_1.8B_ledgar

This model is a fine-tuned version of [Qwen/Qwen1.5-1.8B](https://huggingface.co/Qwen/Qwen1.5-1.8B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5064
- Accuracy: 0.8669
- F1 Macro: 0.7902
- F1 Micro: 0.8669

## 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: 5e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 1.3077        | 0.11  | 100  | 1.0945          | 0.7277   | 0.5771   | 0.7277   |
| 0.8627        | 0.21  | 200  | 0.8368          | 0.7907   | 0.6657   | 0.7907   |
| 0.7179        | 0.32  | 300  | 0.7824          | 0.7971   | 0.6862   | 0.7971   |
| 0.6961        | 0.43  | 400  | 0.6952          | 0.8138   | 0.6992   | 0.8138   |
| 0.745         | 0.53  | 500  | 0.6719          | 0.8121   | 0.7034   | 0.8121   |
| 0.6505        | 0.64  | 600  | 0.6220          | 0.834    | 0.7469   | 0.834    |
| 0.5914        | 0.75  | 700  | 0.6110          | 0.8362   | 0.7411   | 0.8362   |
| 0.5837        | 0.85  | 800  | 0.5767          | 0.8385   | 0.7413   | 0.8385   |
| 0.5218        | 0.96  | 900  | 0.5365          | 0.849    | 0.7703   | 0.849    |
| 0.2632        | 1.07  | 1000 | 0.5504          | 0.8562   | 0.7684   | 0.8562   |
| 0.2607        | 1.17  | 1100 | 0.5497          | 0.8525   | 0.7657   | 0.8525   |
| 0.274         | 1.28  | 1200 | 0.5439          | 0.8584   | 0.7746   | 0.8584   |
| 0.2216        | 1.39  | 1300 | 0.5687          | 0.8563   | 0.7754   | 0.8563   |
| 0.2044        | 1.49  | 1400 | 0.5385          | 0.861    | 0.7820   | 0.861    |
| 0.2508        | 1.6   | 1500 | 0.5658          | 0.8577   | 0.7711   | 0.8577   |
| 0.2513        | 1.71  | 1600 | 0.5367          | 0.8589   | 0.7872   | 0.8589   |
| 0.2787        | 1.81  | 1700 | 0.5133          | 0.8653   | 0.7903   | 0.8653   |
| 0.2357        | 1.92  | 1800 | 0.5064          | 0.8669   | 0.7902   | 0.8669   |
| 0.049         | 2.03  | 1900 | 0.5344          | 0.8719   | 0.7978   | 0.8719   |
| 0.0298        | 2.13  | 2000 | 0.5762          | 0.8737   | 0.7992   | 0.8737   |
| 0.0427        | 2.24  | 2100 | 0.5961          | 0.8708   | 0.7976   | 0.8708   |
| 0.036         | 2.35  | 2200 | 0.6128          | 0.8728   | 0.7988   | 0.8728   |
| 0.0551        | 2.45  | 2300 | 0.6165          | 0.8708   | 0.7976   | 0.8708   |
| 0.0392        | 2.56  | 2400 | 0.6023          | 0.8749   | 0.8038   | 0.8749   |
| 0.0364        | 2.67  | 2500 | 0.6168          | 0.8729   | 0.8001   | 0.8729   |
| 0.0416        | 2.77  | 2600 | 0.6103          | 0.8753   | 0.8048   | 0.8753   |
| 0.0353        | 2.88  | 2700 | 0.6118          | 0.8749   | 0.8054   | 0.8749   |
| 0.0308        | 2.99  | 2800 | 0.6114          | 0.875    | 0.8057   | 0.875    |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2