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bartpho-word-base-ed-multi-v2
cuongpp/bartpho-word-base-ed-multi-v2
bartpho-word-base-ed-multi-v2 is a machine learning model from cuongpp. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- mbart
- Access
- Public
- Created
- Jun 19, 2024
- Updated
- Jun 19, 2024
- SHA
- 261966ba
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. -->
bartpho-word-base-ed-multi-v2
This model is a fine-tuned version of vinai/bartpho-word-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0265
- F1 Micro: 0.8088
- Recall Micro: 0.8070
- Precision Micro: 0.8106
- F1 Macro: 0.6254
- Recall Macro: 0.6672
- Precision Macro: 0.6084
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | Recall Micro | Precision Micro | F1 Macro | Recall Macro | Precision Macro |
|---|---|---|---|---|---|---|---|---|---|
| No log | 0.9987 | 393 | 0.0251 | 0.8059 | 0.8110 | 0.8008 | 0.5082 | 0.5352 | 0.5171 |
| 0.0227 | 2.0 | 787 | 0.0252 | 0.7931 | 0.7957 | 0.7906 | 0.5909 | 0.6664 | 0.5631 |
| 0.017 | 2.9987 | 1180 | 0.0249 | 0.8006 | 0.8036 | 0.7977 | 0.6057 | 0.6286 | 0.6096 |
| 0.013 | 4.0 | 1574 | 0.0260 | 0.8040 | 0.7996 | 0.8085 | 0.6024 | 0.6257 | 0.6028 |
| 0.013 | 4.9936 | 1965 | 0.0265 | 0.8088 | 0.8070 | 0.8106 | 0.6254 | 0.6672 | 0.6084 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Library
- transformers
- Type
- mbart
- Created
- Jun 19, 2024
- Updated
- Jun 19, 2024