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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-76800-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: 0.9414991482921289 |
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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-76800-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: 0.9415 |
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- Acc: 0.9416 |
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- Loss: 0.5192 |
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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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| 0.2328 | 1.0 | 4800 | 0.9289 | 0.9289 | 0.2082 | |
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| 0.2061 | 2.0 | 9600 | 0.9366 | 0.9367 | 0.2154 | |
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| 0.1488 | 3.0 | 14400 | 0.9401 | 0.9401 | 0.2181 | |
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| 0.114 | 4.0 | 19200 | 0.9280 | 0.9275 | 0.3199 | |
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| 0.0818 | 5.0 | 24000 | 0.9399 | 0.94 | 0.2953 | |
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| 0.051 | 6.0 | 28800 | 0.9402 | 0.9403 | 0.3828 | |
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| 0.0413 | 7.0 | 33600 | 0.9404 | 0.9403 | 0.4327 | |
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| 0.0342 | 8.0 | 38400 | 0.9395 | 0.9395 | 0.4291 | |
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| 0.0192 | 9.0 | 43200 | 0.9422 | 0.9422 | 0.4170 | |
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| 0.0204 | 10.0 | 48000 | 0.9374 | 0.9374 | 0.4761 | |
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| 0.0125 | 11.0 | 52800 | 0.9358 | 0.9359 | 0.5126 | |
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| 0.0124 | 12.0 | 57600 | 0.9415 | 0.9416 | 0.5192 | |
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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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