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minilm-fintuned-emotion
arche4452/minilm-fintuned-emotion
minilm-fintuned-emotion is a text classification model from arche4452. 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
- bert
- Access
- Public
- Created
- Nov 14, 2023
- Updated
- Nov 20, 2023
- SHA
- 7baa020b
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Base models
Datasets
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. -->
minilm-fintuned-emotion
This model is a fine-tuned version of microsoft/MiniLM-L12-H384-uncased on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.3649
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 250 | 0.2190 |
| No log | 2.0 | 500 | 0.2935 |
| No log | 3.0 | 750 | 0.2978 |
| No log | 4.0 | 1000 | 0.2842 |
| No log | 5.0 | 1250 | 0.3042 |
| No log | 6.0 | 1500 | 0.3383 |
| No log | 7.0 | 1750 | 0.3491 |
| No log | 8.0 | 2000 | 0.3548 |
| No log | 9.0 | 2250 | 0.3648 |
| No log | 10.0 | 2500 | 0.3649 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Nov 14, 2023
- Updated
- Nov 20, 2023