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efficient_mlm_m0.40-finetuned-classification
ThomasLI/efficient_mlm_m0.40-finetuned-classification
efficient_mlm_m0.40-finetuned-classification is a text classification model from ThomasLI. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta-prelayernorm
- Access
- Public
- Created
- Mar 3, 2023
- Updated
- Mar 3, 2023
- SHA
- fdd1e23a
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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. -->
efficient_mlm_m0.40-finetuned-classification
This model is a fine-tuned version of andreasmadsen/efficient_mlm_m0.40 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4442
- Accuracy: 0.8512
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 200 | 0.6189 | 0.7275 |
| No log | 2.0 | 400 | 0.3894 | 0.8363 |
| 0.5095 | 3.0 | 600 | 0.3870 | 0.8488 |
| 0.5095 | 4.0 | 800 | 0.4055 | 0.8538 |
| 0.23 | 5.0 | 1000 | 0.4442 | 0.8512 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- roberta-prelayernorm
- Created
- Mar 3, 2023
- Updated
- Mar 3, 2023