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intfloat-multilingual-e5-base-english-fp16-allagree
abdulrahman-nuzha/intfloat-multilingual-e5-base-english-fp16-allagree
intfloat-multilingual-e5-base-english-fp16-allagree is a text classification model from abdulrahman-nuzha. 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
- Apr 15, 2025
- Updated
- Apr 15, 2025
- SHA
- 9fa191ee
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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. -->
intfloat-multilingual-e5-base-english-fp16-allagree
This model is a fine-tuned version of intfloat/multilingual-e5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0757
- Accuracy: 0.9780
- Precision: 0.9787
- Recall: 0.9780
- F1: 0.9781
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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.3
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.8202 | 3.3448 | 50 | 0.3822 | 0.8811 | 0.8855 | 0.8811 | 0.8797 |
| 0.1207 | 6.6897 | 100 | 0.0757 | 0.9780 | 0.9787 | 0.9780 | 0.9781 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.6.0+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Apr 15, 2025
- Updated
- Apr 15, 2025