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dnd
mishkashishka/dnd
dnd is a machine learning model from mishkashishka. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Model type
- distilbert
- Access
- Public
- Created
- Aug 13, 2024
- Updated
- Aug 13, 2024
- SHA
- 360c6023
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. -->
dnd
This model is a fine-tuned version of neal49/distilbert-sst2-runglue on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4907
- Accuracy: 0.8246
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-06
- 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: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 15 | 0.6813 | 0.5789 |
| No log | 2.0 | 30 | 0.6725 | 0.5789 |
| No log | 3.0 | 45 | 0.6588 | 0.6140 |
| No log | 4.0 | 60 | 0.6536 | 0.6140 |
| No log | 5.0 | 75 | 0.6524 | 0.6140 |
| No log | 6.0 | 90 | 0.6426 | 0.6140 |
| No log | 7.0 | 105 | 0.6333 | 0.6316 |
| No log | 8.0 | 120 | 0.6148 | 0.6491 |
| No log | 9.0 | 135 | 0.6081 | 0.6491 |
| No log | 10.0 | 150 | 0.5724 | 0.7018 |
| No log | 11.0 | 165 | 0.5984 | 0.6842 |
| No log | 12.0 | 180 | 0.5328 | 0.7368 |
| No log | 13.0 | 195 | 0.5419 | 0.7719 |
| No log | 14.0 | 210 | 0.5271 | 0.7719 |
| No log | 15.0 | 225 | 0.5188 | 0.7719 |
| No log | 16.0 | 240 | 0.5283 | 0.7719 |
| No log | 17.0 | 255 | 0.5012 | 0.7719 |
| No log | 18.0 | 270 | 0.4863 | 0.7895 |
| No log | 19.0 | 285 | 0.5329 | 0.7895 |
| No log | 20.0 | 300 | 0.4861 | 0.8070 |
| No log | 21.0 | 315 | 0.5065 | 0.8246 |
| No log | 22.0 | 330 | 0.4864 | 0.8070 |
| No log | 23.0 | 345 | 0.5060 | 0.8246 |
| No log | 24.0 | 360 | 0.4752 | 0.8246 |
| No log | 25.0 | 375 | 0.4983 | 0.8246 |
| No log | 26.0 | 390 | 0.4925 | 0.8246 |
| No log | 27.0 | 405 | 0.4774 | 0.8246 |
| No log | 28.0 | 420 | 0.4804 | 0.8246 |
| No log | 29.0 | 435 | 0.4927 | 0.8246 |
| No log | 30.0 | 450 | 0.4907 | 0.8246 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.13.2
- Type
- distilbert
- Created
- Aug 13, 2024
- Updated
- Aug 13, 2024