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my_awesome_model
lilyyellow/my_awesome_model
my_awesome_model is a text classification model from lilyyellow. 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
- distilbert
- Access
- Public
- Created
- May 2, 2024
- Updated
- May 6, 2024
- SHA
- eb1d09fa
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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. -->
my_awesome_model
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: 0.0001
- Precision: 0.9890
- Recall: 1.0
- F1: 0.9945
- Accuracy: 1.0000
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0002 | 1.0 | 806 | 0.0007 | 0.7980 | 0.9 | 0.8460 | 0.9996 |
| 0.0001 | 2.0 | 1612 | 0.0002 | 0.9569 | 0.9861 | 0.9713 | 0.9999 |
| 0.0 | 3.0 | 2418 | 0.0001 | 0.9728 | 0.9917 | 0.9821 | 0.9999 |
| 0.0 | 4.0 | 3224 | 0.0001 | 0.9863 | 1.0 | 0.9931 | 1.0000 |
| 0.0 | 5.0 | 4030 | 0.0001 | 0.9890 | 1.0 | 0.9945 | 1.0000 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- mit
- Created
- May 2, 2024
- Updated
- May 6, 2024