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ts_subcate
kmcs-casulit/ts_subcate
ts_subcate is a machine learning model from kmcs-casulit. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- mit
- Model type
- deberta-v2
- Access
- Public
- Created
- Aug 6, 2024
- Updated
- Aug 6, 2024
- SHA
- b6822a36
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
ts_subcate
This model is a fine-tuned version of tangminhanh/ts_cate on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0084
- Accuracy: 0.7013
- F1: 0.7812
- Precision: 0.8815
- Recall: 0.7014
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 | 403 | 0.0261 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.0805 | 2.0 | 806 | 0.0174 | 0.3328 | 0.4904 | 0.9438 | 0.3313 |
| 0.0203 | 3.0 | 1209 | 0.0131 | 0.4702 | 0.6217 | 0.9229 | 0.4687 |
| 0.0138 | 4.0 | 1612 | 0.0111 | 0.5592 | 0.6939 | 0.9170 | 0.5581 |
| 0.0104 | 5.0 | 2015 | 0.0100 | 0.6297 | 0.7417 | 0.8998 | 0.6308 |
| 0.0104 | 6.0 | 2418 | 0.0091 | 0.6659 | 0.7628 | 0.8909 | 0.6669 |
| 0.0084 | 7.0 | 2821 | 0.0088 | 0.6815 | 0.7712 | 0.8867 | 0.6823 |
| 0.0072 | 8.0 | 3224 | 0.0086 | 0.6889 | 0.7764 | 0.8874 | 0.6900 |
| 0.0063 | 9.0 | 3627 | 0.0084 | 0.6982 | 0.7803 | 0.8832 | 0.6989 |
| 0.006 | 10.0 | 4030 | 0.0084 | 0.7013 | 0.7812 | 0.8815 | 0.7014 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- deberta-v2
- License
- mit
- Created
- Aug 6, 2024
- Updated
- Aug 6, 2024