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scenario-TCR-XLMV-1_data-AmazonScience_massive_all_1_1
haryoaw/scenario-TCR-XLMV-1_data-AmazonScience_massive_all_1_1
scenario-TCR-XLMV-1_data-AmazonScience_massive_all_1_1 is a text classification model from haryoaw. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Mar 8, 2024
- Updated
- Mar 8, 2024
- SHA
- 50166673
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Base models
Datasets
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. -->
scenario-TCR-XLMV-1_data-AmazonScience_massive_all_1_1
This model is a fine-tuned version of facebook/xlm-v-base on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.7886
- Accuracy: 0.8473
- F1: 0.8226
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-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 47
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 500
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.587 | 0.27 | 5000 | 0.7148 | 0.8166 | 0.7696 |
| 0.456 | 0.53 | 10000 | 0.6624 | 0.8415 | 0.8006 |
| 0.3711 | 0.8 | 15000 | 0.6803 | 0.8394 | 0.8064 |
| 0.2846 | 1.07 | 20000 | 0.7409 | 0.8406 | 0.8119 |
| 0.2698 | 1.34 | 25000 | 0.7120 | 0.8428 | 0.8129 |
| 0.2589 | 1.6 | 30000 | 0.7179 | 0.8478 | 0.8300 |
| 0.246 | 1.87 | 35000 | 0.7383 | 0.8455 | 0.8119 |
| 0.2079 | 2.14 | 40000 | 0.7911 | 0.8503 | 0.8162 |
| 0.2157 | 2.41 | 45000 | 0.7775 | 0.8434 | 0.8251 |
| 0.2111 | 2.67 | 50000 | 0.7737 | 0.8455 | 0.8196 |
| 0.2014 | 2.94 | 55000 | 0.7886 | 0.8473 | 0.8226 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Mar 8, 2024
- Updated
- Mar 8, 2024