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---
license: other
base_model: Qwen/Qwen1.5-1.8B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Qwen1.5_1.8B_twitter
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_twitter
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: 0.5039
- Accuracy: 0.7776
- F1 Macro: 0.7420
- F1 Micro: 0.7776
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 0.6585 | 0.18 | 50 | 0.6435 | 0.7123 | 0.5811 | 0.7123 |
| 0.6396 | 0.37 | 100 | 0.6016 | 0.7298 | 0.6998 | 0.7298 |
| 0.5108 | 0.55 | 150 | 0.5227 | 0.7528 | 0.6963 | 0.7528 |
| 0.5065 | 0.74 | 200 | 0.5503 | 0.7417 | 0.6347 | 0.7417 |
| 0.4883 | 0.92 | 250 | 0.5039 | 0.7776 | 0.7420 | 0.7776 |
| 0.3296 | 1.1 | 300 | 0.5250 | 0.7730 | 0.7307 | 0.7730 |
| 0.322 | 1.29 | 350 | 0.5510 | 0.7721 | 0.7423 | 0.7721 |
| 0.3287 | 1.47 | 400 | 0.5392 | 0.7583 | 0.6932 | 0.7583 |
| 0.3097 | 1.65 | 450 | 0.5631 | 0.7629 | 0.7223 | 0.7629 |
| 0.3397 | 1.84 | 500 | 0.5669 | 0.7675 | 0.7334 | 0.7675 |
| 0.2618 | 2.02 | 550 | 0.5891 | 0.75 | 0.6870 | 0.75 |
| 0.1745 | 2.21 | 600 | 0.6400 | 0.7583 | 0.7123 | 0.7583 |
| 0.1572 | 2.39 | 650 | 0.6694 | 0.7518 | 0.6967 | 0.7518 |
| 0.1804 | 2.57 | 700 | 0.6870 | 0.7610 | 0.7173 | 0.7610 |
| 0.1817 | 2.76 | 750 | 0.6656 | 0.7537 | 0.7045 | 0.7537 |
| 0.1984 | 2.94 | 800 | 0.6783 | 0.7518 | 0.6949 | 0.7518 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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