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Vic_model_3ep
adriansanz/Vic_model_3ep
Vic_model_3ep is a text classification model from adriansanz. 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
- Jul 30, 2024
- Updated
- Jul 30, 2024
- SHA
- e082922c
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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. -->
Vic_model
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3819
- Accuracy: 0.9214
- Precision: 0.9218
- Recall: 0.9214
- F1: 0.9207
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.7251 | 1.0 | 1225 | 0.5471 | 0.8343 | 0.8489 | 0.8343 | 0.8321 |
| 0.4312 | 2.0 | 2450 | 0.4058 | 0.8986 | 0.9000 | 0.8986 | 0.8974 |
| 0.1904 | 3.0 | 3675 | 0.3819 | 0.9214 | 0.9218 | 0.9214 | 0.9207 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Jul 30, 2024
- Updated
- Jul 30, 2024