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scenario-TCR-XLMV-4_data-AmazonScience_massive_all_1_1
haryoaw/scenario-TCR-XLMV-4_data-AmazonScience_massive_all_1_1
scenario-TCR-XLMV-4_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
- a14dc768
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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-4_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: 0.8322
- Accuracy: 0.8462
- F1: 0.8244
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: 777
- 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 |
|---|---|---|---|---|---|
| 0.595 | 0.27 | 5000 | 0.7040 | 0.8241 | 0.7720 |
| 0.4654 | 0.53 | 10000 | 0.6468 | 0.8410 | 0.8027 |
| 0.3838 | 0.8 | 15000 | 0.6802 | 0.8399 | 0.7994 |
| 0.2831 | 1.07 | 20000 | 0.7290 | 0.8471 | 0.8206 |
| 0.274 | 1.34 | 25000 | 0.7192 | 0.8471 | 0.8141 |
| 0.2598 | 1.6 | 30000 | 0.7145 | 0.8440 | 0.8215 |
| 0.2501 | 1.87 | 35000 | 0.7347 | 0.8500 | 0.8245 |
| 0.2022 | 2.14 | 40000 | 0.7809 | 0.8503 | 0.8223 |
| 0.2164 | 2.41 | 45000 | 0.7481 | 0.8533 | 0.8280 |
| 0.2008 | 2.67 | 50000 | 0.7684 | 0.8467 | 0.8252 |
| 0.2015 | 2.94 | 55000 | 0.8170 | 0.8422 | 0.8160 |
| 0.1716 | 3.21 | 60000 | 0.8603 | 0.8433 | 0.8186 |
| 0.1643 | 3.47 | 65000 | 0.8221 | 0.8514 | 0.8279 |
| 0.1816 | 3.74 | 70000 | 0.8322 | 0.8462 | 0.8244 |
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