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---
license: mit
base_model: tangminhanh/ts_subcate
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: cs_subcate
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. -->
# cs_subcate
This model is a fine-tuned version of [tangminhanh/ts_subcate](https://huggingface.co/tangminhanh/ts_subcate) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0517
- Accuracy: 0.6283
- F1: 0.6777
- Precision: 0.7292
- Recall: 0.6330
## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log | 1.0 | 195 | 0.0649 | 0.2715 | 0.4110 | 0.8554 | 0.2704 |
| No log | 2.0 | 390 | 0.0532 | 0.5113 | 0.6149 | 0.7639 | 0.5145 |
| 0.0785 | 3.0 | 585 | 0.0515 | 0.5688 | 0.6404 | 0.7225 | 0.5750 |
| 0.0785 | 4.0 | 780 | 0.0496 | 0.5979 | 0.6606 | 0.7225 | 0.6085 |
| 0.0785 | 5.0 | 975 | 0.0492 | 0.6147 | 0.6753 | 0.7367 | 0.6233 |
| 0.0386 | 6.0 | 1170 | 0.0499 | 0.6141 | 0.6701 | 0.7151 | 0.6304 |
| 0.0386 | 7.0 | 1365 | 0.0503 | 0.6206 | 0.6754 | 0.7265 | 0.6310 |
| 0.0283 | 8.0 | 1560 | 0.0512 | 0.6199 | 0.6717 | 0.7129 | 0.6349 |
| 0.0283 | 9.0 | 1755 | 0.0515 | 0.6193 | 0.6720 | 0.7228 | 0.6278 |
| 0.0283 | 10.0 | 1950 | 0.0517 | 0.6283 | 0.6777 | 0.7292 | 0.6330 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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