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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imdb |
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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: bert_uncased_L-2_H-128_A-2-finetuned-emotion-finetuned-tweet |
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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: imdb |
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type: imdb |
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config: plain_text |
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split: train |
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args: plain_text |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.87168 |
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- name: F1 |
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type: f1 |
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value: 0.8716747437975058 |
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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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# bert_uncased_L-2_H-128_A-2-finetuned-emotion-finetuned-tweet |
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This model is a fine-tuned version of [muhtasham/bert_uncased_L-2_H-128_A-2-finetuned-emotion](https://huggingface.co/muhtasham/bert_uncased_L-2_H-128_A-2-finetuned-emotion) on the imdb dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4004 |
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- Accuracy: 0.8717 |
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- F1: 0.8717 |
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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: 3e-05 |
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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: constant |
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- num_epochs: 200 |
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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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| 0.4751 | 1.28 | 500 | 0.3880 | 0.828 | 0.8277 | |
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| 0.3453 | 2.56 | 1000 | 0.3282 | 0.8608 | 0.8607 | |
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| 0.2973 | 3.84 | 1500 | 0.3140 | 0.8695 | 0.8695 | |
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| 0.26 | 5.12 | 2000 | 0.3154 | 0.8736 | 0.8735 | |
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| 0.2218 | 6.39 | 2500 | 0.3144 | 0.8756 | 0.8756 | |
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| 0.1977 | 7.67 | 3000 | 0.3197 | 0.876 | 0.8760 | |
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| 0.1656 | 8.95 | 3500 | 0.3526 | 0.8737 | 0.8735 | |
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| 0.1404 | 10.23 | 4000 | 0.3865 | 0.8691 | 0.8689 | |
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| 0.121 | 11.51 | 4500 | 0.4004 | 0.8717 | 0.8717 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.7.0 |
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- Tokenizers 0.13.2 |
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