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---
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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model-index:
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- name: electra-large-discriminator-nli-efl-hateval
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# electra-large-discriminator-nli-efl-hateval
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This model is a fine-tuned version of [ynie/electra-large-discriminator-snli_mnli_fever_anli_R1_R2_R3-nli](https://huggingface.co/ynie/electra-large-discriminator-snli_mnli_fever_anli_R1_R2_R3-nli) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4166
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- Accuracy: 0.798
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- F1: 0.7968
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-06
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 20
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 0.4175 | 1.0 | 210 | 0.4020 | 0.7317 | 0.7305 |
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| 0.3061 | 2.0 | 420 | 0.3520 | 0.768 | 0.7675 |
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| 0.2588 | 3.0 | 630 | 0.3253 | 0.79 | 0.7888 |
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| 0.234 | 4.0 | 840 | 0.3373 | 0.788 | 0.7877 |
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| 0.2116 | 5.0 | 1050 | 0.3247 | 0.804 | 0.8033 |
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| 0.1974 | 6.0 | 1260 | 0.3400 | 0.793 | 0.7928 |
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| 0.1807 | 7.0 | 1470 | 0.3511 | 0.7973 | 0.7969 |
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| 0.1715 | 8.0 | 1680 | 0.3496 | 0.7993 | 0.7989 |
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| 0.1577 | 9.0 | 1890 | 0.3507 | 0.8043 | 0.8032 |
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| 0.1469 | 10.0 | 2100 | 0.3604 | 0.798 | 0.7970 |
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| 0.1394 | 11.0 | 2310 | 0.3734 | 0.7967 | 0.7957 |
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| 0.1322 | 12.0 | 2520 | 0.3929 | 0.7913 | 0.7906 |
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| 0.1231 | 13.0 | 2730 | 0.3954 | 0.795 | 0.7941 |
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| 0.1189 | 14.0 | 2940 | 0.3994 | 0.7977 | 0.7963 |
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| 0.1143 | 15.0 | 3150 | 0.3995 | 0.7993 | 0.7980 |
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| 0.1083 | 16.0 | 3360 | 0.4125 | 0.7927 | 0.7918 |
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| 0.1079 | 17.0 | 3570 | 0.4036 | 0.7993 | 0.7979 |
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| 0.1055 | 18.0 | 3780 | 0.4121 | 0.7967 | 0.7956 |
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| 0.1006 | 19.0 | 3990 | 0.4152 | 0.7973 | 0.7961 |
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| 0.101 | 20.0 | 4200 | 0.4166 | 0.798 | 0.7968 |
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 1.11.0+cu113
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- Datasets 2.0.0
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- Tokenizers 0.11.6
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