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electricidad-small-finetuned-diagTrast
mrm8488/electricidad-small-finetuned-diagTrast
electricidad-small-finetuned-diagTrast is a text classification model from mrm8488. 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
- electra
- Access
- Public
- Created
- Apr 5, 2023
- Updated
- Apr 5, 2023
- SHA
- bf9c2df9
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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. -->
electricidad (small) fine-tuned diagTrast
This model is a fine-tuned version of mrm8488/electricidad-small-discriminator on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2070
- Precision: 0.9349
- Recall: 0.9328
- Accuracy: 0.9328
- F1: 0.9330
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: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 14
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 150 | 1.4344 | 0.6909 | 0.6045 | 0.6045 | 0.5460 |
| No log | 2.0 | 300 | 1.1666 | 0.8055 | 0.7537 | 0.7537 | 0.7211 |
| No log | 3.0 | 450 | 0.9593 | 0.8321 | 0.8134 | 0.8134 | 0.7913 |
| 1.2831 | 4.0 | 600 | 0.7721 | 0.8575 | 0.8433 | 0.8433 | 0.8257 |
| 1.2831 | 5.0 | 750 | 0.6225 | 0.9062 | 0.9030 | 0.9030 | 0.9009 |
| 1.2831 | 6.0 | 900 | 0.4790 | 0.9179 | 0.9179 | 0.9179 | 0.9168 |
| 0.595 | 7.0 | 1050 | 0.3886 | 0.9340 | 0.9328 | 0.9328 | 0.9327 |
| 0.595 | 8.0 | 1200 | 0.3241 | 0.9258 | 0.9254 | 0.9254 | 0.9248 |
| 0.595 | 9.0 | 1350 | 0.2958 | 0.9198 | 0.9179 | 0.9179 | 0.9175 |
| 0.2183 | 10.0 | 1500 | 0.2469 | 0.9191 | 0.9179 | 0.9179 | 0.9175 |
| 0.2183 | 11.0 | 1650 | 0.2352 | 0.9195 | 0.9179 | 0.9179 | 0.9176 |
| 0.2183 | 12.0 | 1800 | 0.2118 | 0.9262 | 0.9254 | 0.9254 | 0.9249 |
| 0.2183 | 13.0 | 1950 | 0.2138 | 0.9195 | 0.9179 | 0.9179 | 0.9176 |
| 0.0984 | 14.0 | 2100 | 0.2070 | 0.9349 | 0.9328 | 0.9328 | 0.9330 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- electra
- Created
- Apr 5, 2023
- Updated
- Apr 5, 2023