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--- |
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license: apache-2.0 |
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base_model: google/electra-small-discriminator |
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tags: |
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- generated_from_trainer |
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datasets: |
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- tweet_eval |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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model-index: |
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- name: electra-3-epoch-sentiment |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: tweet_eval |
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type: tweet_eval |
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config: sentiment |
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split: test |
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args: sentiment |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.6884565288179746 |
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- name: Precision |
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type: precision |
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value: 0.6917205994992218 |
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- name: Recall |
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type: recall |
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value: 0.6884565288179746 |
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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-3-epoch-sentiment |
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This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the tweet_eval dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7153 |
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- Accuracy: 0.6885 |
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- Precision: 0.6917 |
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- Recall: 0.6885 |
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- Micro-avg-recall: 0.6885 |
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- Micro-avg-precision: 0.6885 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Micro-avg-recall | Micro-avg-precision | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:----------------:|:-------------------:| |
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| 0.6307 | 1.0 | 2851 | 0.6867 | 0.6997 | 0.6998 | 0.6997 | 0.6997 | 0.6997 | |
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| 0.6717 | 2.0 | 5702 | 0.7312 | 0.6820 | 0.6877 | 0.6820 | 0.6820 | 0.6820 | |
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| 0.5799 | 3.0 | 8553 | 0.7153 | 0.6885 | 0.6917 | 0.6885 | 0.6885 | 0.6885 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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