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

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: 1.6403
- Accuracy: 0.515
- F1 Macro: 0.3569
- F1 Micro: 0.515

## 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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 2.1746        | 0.32  | 50   | 2.2792          | 0.2693   | 0.1148   | 0.2693   |
| 1.5758        | 0.64  | 100  | 1.9309          | 0.41     | 0.2291   | 0.41     |
| 1.7312        | 0.96  | 150  | 1.7475          | 0.4714   | 0.2547   | 0.4714   |
| 1.2859        | 1.27  | 200  | 1.7939          | 0.4686   | 0.3019   | 0.4686   |
| 1.1971        | 1.59  | 250  | 1.7146          | 0.4957   | 0.3307   | 0.4957   |
| 1.1271        | 1.91  | 300  | 1.6403          | 0.515    | 0.3569   | 0.515    |
| 0.8436        | 2.23  | 350  | 1.7995          | 0.51     | 0.3717   | 0.51     |
| 0.7723        | 2.55  | 400  | 1.8401          | 0.5029   | 0.3723   | 0.5029   |
| 0.7211        | 2.87  | 450  | 1.8232          | 0.5179   | 0.3753   | 0.5179   |


### Framework versions

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