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vmw-xlm-focal-lr-3e-5
jaycentg/vmw-xlm-focal-lr-3e-5
vmw-xlm-focal-lr-3e-5 is a text classification model from jaycentg. 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
- Jan 23, 2025
- Updated
- Jan 23, 2025
- SHA
- 20a1fadc
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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. -->
vmw-xlm-focal-lr-3e-5
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 7.9885
- F1-micro: 0.1783
- F1-macro: 0.1212
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 30
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | F1-micro | F1-macro |
|---|---|---|---|---|---|
| 23.4304 | 1.0 | 78 | 7.9835 | 0.1312 | 0.1120 |
| 23.1213 | 2.0 | 156 | 7.9505 | 0.1327 | 0.1032 |
| 23.3218 | 3.0 | 234 | 7.9915 | 0.1841 | 0.1235 |
| 23.0612 | 4.0 | 312 | 7.9885 | 0.1783 | 0.1212 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Jan 23, 2025
- Updated
- Jan 23, 2025