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phobert-base-v2-finetuned_60kURL
gechim/phobert-base-v2-finetuned_60kURL
phobert-base-v2-finetuned_60kURL is a text classification model from gechim. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- May 27, 2024
- Updated
- May 27, 2024
- SHA
- 74b64e54
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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. -->
phobert-base-v2-finetuned-finetuned_60kURL
This model is a fine-tuned version of gechim/phobert-base-v2-finetuned on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3594
- Accuracy: 0.9562
- F1: 0.9563
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.1679 | 1.0 | 704 | 0.1285 | 0.9549 | 0.9552 |
| 0.1111 | 2.0 | 1408 | 0.1405 | 0.9529 | 0.9526 |
| 0.0888 | 3.0 | 2112 | 0.1392 | 0.9592 | 0.9592 |
| 0.0721 | 4.0 | 2816 | 0.1433 | 0.9561 | 0.9564 |
| 0.059 | 5.0 | 3520 | 0.1563 | 0.9584 | 0.9586 |
| 0.0486 | 6.0 | 4224 | 0.1719 | 0.9549 | 0.9552 |
| 0.0399 | 7.0 | 4928 | 0.2006 | 0.9561 | 0.9563 |
| 0.0316 | 8.0 | 5632 | 0.2461 | 0.9553 | 0.9555 |
| 0.0269 | 9.0 | 6336 | 0.2424 | 0.9556 | 0.9557 |
| 0.0242 | 10.0 | 7040 | 0.2686 | 0.9543 | 0.9543 |
| 0.0202 | 11.0 | 7744 | 0.2813 | 0.9559 | 0.9559 |
| 0.0153 | 12.0 | 8448 | 0.2984 | 0.9563 | 0.9564 |
| 0.012 | 13.0 | 9152 | 0.3171 | 0.9553 | 0.9555 |
| 0.009 | 14.0 | 9856 | 0.3452 | 0.9549 | 0.9549 |
| 0.0088 | 15.0 | 10560 | 0.3415 | 0.9570 | 0.9571 |
| 0.008 | 16.0 | 11264 | 0.3374 | 0.9564 | 0.9564 |
| 0.0064 | 17.0 | 11968 | 0.3490 | 0.9564 | 0.9565 |
| 0.0054 | 18.0 | 12672 | 0.3598 | 0.9560 | 0.9561 |
| 0.0057 | 19.0 | 13376 | 0.3595 | 0.9559 | 0.9559 |
| 0.0044 | 20.0 | 14080 | 0.3594 | 0.9562 | 0.9563 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- May 27, 2024
- Updated
- May 27, 2024