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--- |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- ag_news |
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metrics: |
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- f1 |
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model-index: |
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- name: ag-news-twitter-9600-bert-base-uncased |
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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: ag_news |
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type: ag_news |
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config: default |
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split: test |
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args: default |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.9162249767982196 |
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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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# ag-news-twitter-9600-bert-base-uncased |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the ag_news dataset. |
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It achieves the following results on the evaluation set: |
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- F1: 0.9162 |
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- Acc: 0.9162 |
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- Loss: 0.6033 |
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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: 8 |
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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_ratio: 0.1 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | F1 | Acc | Validation Loss | |
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|:-------------:|:-----:|:----:|:------:|:------:|:---------------:| |
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| 0.8065 | 1.0 | 600 | 0.9060 | 0.9059 | 0.3013 | |
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| 0.2872 | 2.0 | 1200 | 0.9171 | 0.9170 | 0.2598 | |
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| 0.2156 | 3.0 | 1800 | 0.9178 | 0.9184 | 0.3117 | |
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| 0.1486 | 4.0 | 2400 | 0.9200 | 0.9197 | 0.3631 | |
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| 0.0683 | 5.0 | 3000 | 0.9202 | 0.9201 | 0.3782 | |
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| 0.045 | 6.0 | 3600 | 0.9186 | 0.9188 | 0.4846 | |
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| 0.0218 | 7.0 | 4200 | 0.9155 | 0.9155 | 0.5898 | |
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| 0.0245 | 8.0 | 4800 | 0.9162 | 0.9162 | 0.6033 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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