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tinybert-roberta-meld-distilled
Rudra2002019/tinybert-roberta-meld-distilled
tinybert-roberta-meld-distilled is a text classification model from Rudra2002019. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- May 18, 2025
- Updated
- May 18, 2025
- SHA
- d8bffee6
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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. -->
tinybert-roberta-meld-distilled
This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6964
- Accuracy: 0.1322
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: 4e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- 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
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.2613 | 1.0 | 79 | 2.0125 | 0.1322 |
| 1.9306 | 2.0 | 158 | 1.8266 | 0.1322 |
| 1.8039 | 3.0 | 237 | 1.7391 | 0.1322 |
| 1.7476 | 4.0 | 316 | 1.7046 | 0.1322 |
| 1.7296 | 5.0 | 395 | 1.6964 | 0.1322 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- May 18, 2025
- Updated
- May 18, 2025