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--- |
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license: apache-2.0 |
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base_model: google/electra-base-discriminator |
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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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- precision |
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- recall |
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model-index: |
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- name: electra-base-discriminator_Synonym-wordnet |
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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-base-discriminator_Synonym-wordnet |
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This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2211 |
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- Accuracy: 0.9267 |
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- F1: 0.9267 |
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- Precision: 0.9267 |
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- Recall: 0.9267 |
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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: 0.0001 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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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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- lr_scheduler_warmup_steps: 1000 |
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- num_epochs: 25 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.932 | 1.0 | 91 | 0.8735 | 0.6412 | 0.5915 | 0.6417 | 0.6412 | |
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| 0.426 | 2.0 | 182 | 0.3389 | 0.9002 | 0.9004 | 0.9008 | 0.9002 | |
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| 0.259 | 3.0 | 273 | 0.2577 | 0.9048 | 0.9039 | 0.9070 | 0.9048 | |
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| 0.1619 | 4.0 | 364 | 0.2211 | 0.9267 | 0.9267 | 0.9267 | 0.9267 | |
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| 0.1574 | 5.0 | 455 | 0.3301 | 0.8955 | 0.8959 | 0.9045 | 0.8955 | |
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| 0.0929 | 6.0 | 546 | 0.3284 | 0.9064 | 0.9054 | 0.9066 | 0.9064 | |
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| 0.1079 | 7.0 | 637 | 0.3467 | 0.9002 | 0.9003 | 0.9040 | 0.9002 | |
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| 0.0927 | 8.0 | 728 | 0.3817 | 0.9002 | 0.8993 | 0.9056 | 0.9002 | |
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| 0.0876 | 9.0 | 819 | 0.3524 | 0.9048 | 0.9044 | 0.9047 | 0.9048 | |
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### Framework versions |
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- Transformers 4.37.0 |
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- Pytorch 2.1.2 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.1 |
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