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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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- Accuracy: 0.798 |
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- F1: 0.7968 |
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- Loss: 0.4166 |
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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 | Accuracy | F1 | Validation Loss | |
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|:-------------:|:-----:|:----:|:--------:|:------:|:---------------:| |
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| 0.4175 | 1.0 | 210 | 0.7317 | 0.7305 | 0.4020 | |
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| 0.3061 | 2.0 | 420 | 0.768 | 0.7675 | 0.3520 | |
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| 0.2588 | 3.0 | 630 | 0.79 | 0.7888 | 0.3253 | |
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| 0.234 | 4.0 | 840 | 0.788 | 0.7877 | 0.3373 | |
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| 0.2116 | 5.0 | 1050 | 0.804 | 0.8033 | 0.3247 | |
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| 0.1974 | 6.0 | 1260 | 0.793 | 0.7928 | 0.3400 | |
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| 0.1807 | 7.0 | 1470 | 0.7973 | 0.7969 | 0.3511 | |
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| 0.1715 | 8.0 | 1680 | 0.7993 | 0.7989 | 0.3496 | |
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| 0.1577 | 9.0 | 1890 | 0.8043 | 0.8032 | 0.3507 | |
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| 0.1469 | 10.0 | 2100 | 0.798 | 0.7970 | 0.3604 | |
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| 0.1394 | 11.0 | 2310 | 0.7967 | 0.7957 | 0.3734 | |
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| 0.1322 | 12.0 | 2520 | 0.7913 | 0.7906 | 0.3929 | |
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| 0.1231 | 13.0 | 2730 | 0.795 | 0.7941 | 0.3954 | |
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| 0.1189 | 14.0 | 2940 | 0.7977 | 0.7963 | 0.3994 | |
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| 0.1143 | 15.0 | 3150 | 0.7993 | 0.7980 | 0.3995 | |
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| 0.1083 | 16.0 | 3360 | 0.7927 | 0.7918 | 0.4125 | |
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| 0.1079 | 17.0 | 3570 | 0.7993 | 0.7979 | 0.4036 | |
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| 0.1055 | 18.0 | 3780 | 0.7967 | 0.7956 | 0.4121 | |
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| 0.1006 | 19.0 | 3990 | 0.7973 | 0.7961 | 0.4152 | |
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| 0.101 | 20.0 | 4200 | 0.798 | 0.7968 | 0.4166 | |
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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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