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electra-large-discriminator-nli-efl-hateval
ChrisZeng/electra-large-discriminator-nli-efl-hateval
electra-large-discriminator-nli-efl-hateval is a text classification model from ChrisZeng. 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 11, 2022
- Updated
- Apr 11, 2022
- SHA
- a6f0d7f8
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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. -->
electra-large-discriminator-nli-efl-hateval
This model is a fine-tuned version of ynie/electra-large-discriminator-snli_mnli_fever_anli_R1_R2_R3-nli on the None dataset. It achieves the following results on the evaluation set:
- Accuracy: 0.798
- F1: 0.7968
- Loss: 0.4166
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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Accuracy | F1 | Validation Loss |
|---|---|---|---|---|---|
| 0.4175 | 1.0 | 210 | 0.7317 | 0.7305 | 0.4020 |
| 0.3061 | 2.0 | 420 | 0.768 | 0.7675 | 0.3520 |
| 0.2588 | 3.0 | 630 | 0.79 | 0.7888 | 0.3253 |
| 0.234 | 4.0 | 840 | 0.788 | 0.7877 | 0.3373 |
| 0.2116 | 5.0 | 1050 | 0.804 | 0.8033 | 0.3247 |
| 0.1974 | 6.0 | 1260 | 0.793 | 0.7928 | 0.3400 |
| 0.1807 | 7.0 | 1470 | 0.7973 | 0.7969 | 0.3511 |
| 0.1715 | 8.0 | 1680 | 0.7993 | 0.7989 | 0.3496 |
| 0.1577 | 9.0 | 1890 | 0.8043 | 0.8032 | 0.3507 |
| 0.1469 | 10.0 | 2100 | 0.798 | 0.7970 | 0.3604 |
| 0.1394 | 11.0 | 2310 | 0.7967 | 0.7957 | 0.3734 |
| 0.1322 | 12.0 | 2520 | 0.7913 | 0.7906 | 0.3929 |
| 0.1231 | 13.0 | 2730 | 0.795 | 0.7941 | 0.3954 |
| 0.1189 | 14.0 | 2940 | 0.7977 | 0.7963 | 0.3994 |
| 0.1143 | 15.0 | 3150 | 0.7993 | 0.7980 | 0.3995 |
| 0.1083 | 16.0 | 3360 | 0.7927 | 0.7918 | 0.4125 |
| 0.1079 | 17.0 | 3570 | 0.7993 | 0.7979 | 0.4036 |
| 0.1055 | 18.0 | 3780 | 0.7967 | 0.7956 | 0.4121 |
| 0.1006 | 19.0 | 3990 | 0.7973 | 0.7961 | 0.4152 |
| 0.101 | 20.0 | 4200 | 0.798 | 0.7968 | 0.4166 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 2.0.0
- Tokenizers 0.11.6
- Task
- Text Classification
- Library
- transformers
- Type
- electra
- Created
- Apr 11, 2022
- Updated
- Apr 11, 2022