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afr-xlm
jaycentg/afr-xlm
afr-xlm 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 14, 2025
- Updated
- Jan 14, 2025
- SHA
- 6cae962f
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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. -->
afr-xlm
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: 0.4735
- F1-micro: 0.4950
- F1-macro: 0.0998
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: 1.5e-06
- 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: 24
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | F1-micro | F1-macro |
|---|---|---|---|---|---|
| 0.688 | 1.0 | 62 | 0.5971 | 0.4953 | 0.1007 |
| 0.5864 | 2.0 | 124 | 0.5503 | 0.5036 | 0.1007 |
| 0.5265 | 3.0 | 186 | 0.4710 | 0.5036 | 0.1009 |
| 0.5042 | 4.0 | 248 | 0.4735 | 0.4950 | 0.0998 |
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 14, 2025
- Updated
- Jan 14, 2025