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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-tweeteval |
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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-tweeteval |
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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: 0.7943 |
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- F1: 0.7872 |
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- Loss: 0.3004 |
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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: 10 |
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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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| 0.4384 | 1.0 | 163 | 0.7444 | 0.7308 | 0.3962 | |
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| 0.3447 | 2.0 | 326 | 0.7659 | 0.7552 | 0.3410 | |
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| 0.3057 | 3.0 | 489 | 0.7750 | 0.7688 | 0.3234 | |
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| 0.287 | 4.0 | 652 | 0.7857 | 0.7779 | 0.3069 | |
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| 0.2742 | 5.0 | 815 | 0.7887 | 0.7822 | 0.3030 | |
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| 0.2676 | 6.0 | 978 | 0.7939 | 0.7851 | 0.2982 | |
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| 0.2585 | 7.0 | 1141 | 0.7909 | 0.7822 | 0.3002 | |
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| 0.2526 | 8.0 | 1304 | 0.7943 | 0.7876 | 0.3052 | |
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| 0.2479 | 9.0 | 1467 | 0.7939 | 0.7847 | 0.2997 | |
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| 0.2451 | 10.0 | 1630 | 0.7956 | 0.7873 | 0.3014 | |
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| 0.2397 | 11.0 | 1793 | 0.7943 | 0.7872 | 0.3004 | |
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### Framework versions |
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- Transformers 4.16.2 |
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- Pytorch 1.12.0.dev20220417 |
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- Datasets 2.1.0 |
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- Tokenizers 0.10.3 |
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