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

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: 0.8989
- Accuracy: 0.6976
- F1 Macro: 0.6507
- F1 Micro: 0.6976

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 1.4469        | 0.13  | 50   | 1.3521          | 0.528    | 0.3842   | 0.528    |
| 1.1465        | 0.26  | 100  | 1.1614          | 0.596    | 0.4991   | 0.596    |
| 1.1717        | 0.38  | 150  | 1.0561          | 0.6286   | 0.5523   | 0.6286   |
| 0.9861        | 0.51  | 200  | 0.9592          | 0.6682   | 0.5813   | 0.6682   |
| 0.9701        | 0.64  | 250  | 0.9579          | 0.6658   | 0.5949   | 0.6658   |
| 0.9389        | 0.77  | 300  | 0.9364          | 0.679    | 0.6287   | 0.679    |
| 0.9914        | 0.9   | 350  | 0.9246          | 0.6756   | 0.6115   | 0.6756   |
| 0.7508        | 1.02  | 400  | 0.9047          | 0.6812   | 0.6406   | 0.6812   |
| 0.6312        | 1.15  | 450  | 0.9342          | 0.6844   | 0.6410   | 0.6844   |
| 0.6436        | 1.28  | 500  | 0.9464          | 0.6848   | 0.6410   | 0.6848   |
| 0.6429        | 1.41  | 550  | 0.9366          | 0.6846   | 0.6299   | 0.6846   |
| 0.6471        | 1.53  | 600  | 0.9347          | 0.6812   | 0.6490   | 0.6812   |
| 0.7045        | 1.66  | 650  | 0.9457          | 0.6696   | 0.6265   | 0.6696   |
| 0.6311        | 1.79  | 700  | 0.9206          | 0.6924   | 0.6303   | 0.6924   |
| 0.6659        | 1.92  | 750  | 0.8989          | 0.6976   | 0.6507   | 0.6976   |
| 0.2872        | 2.05  | 800  | 1.0101          | 0.6888   | 0.6524   | 0.6888   |
| 0.2666        | 2.17  | 850  | 1.1459          | 0.6824   | 0.6384   | 0.6824   |
| 0.3211        | 2.3   | 900  | 1.1165          | 0.6704   | 0.6362   | 0.6704   |
| 0.2831        | 2.43  | 950  | 1.1722          | 0.6698   | 0.6360   | 0.6698   |
| 0.2545        | 2.56  | 1000 | 1.2073          | 0.6714   | 0.6459   | 0.6714   |
| 0.2069        | 2.69  | 1050 | 1.1839          | 0.6798   | 0.6438   | 0.6798   |
| 0.2109        | 2.81  | 1100 | 1.1677          | 0.6778   | 0.6443   | 0.6778   |
| 0.2383        | 2.94  | 1150 | 1.1807          | 0.6776   | 0.6462   | 0.6776   |


### Framework versions

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