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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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- sibyl |
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datasets: |
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- yahoo_answers_topics |
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metrics: |
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- accuracy |
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model-index: |
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- name: bert-base-uncased-yahoo_answers_topics |
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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: yahoo_answers_topics |
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type: yahoo_answers_topics |
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args: yahoo_answers_topics |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7499166666666667 |
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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-base-uncased-yahoo_answers_topics |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the yahoo_answers_topics dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8092 |
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- Accuracy: 0.7499 |
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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: 5e-05 |
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- train_batch_size: 8 |
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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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- lr_scheduler_warmup_steps: 86625 |
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- training_steps: 866250 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 2.162 | 0.01 | 2000 | 1.7444 | 0.5681 | |
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| 1.3126 | 0.02 | 4000 | 1.0081 | 0.7054 | |
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| 0.9592 | 0.03 | 6000 | 0.9021 | 0.7234 | |
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| 0.8903 | 0.05 | 8000 | 0.8827 | 0.7276 | |
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| 0.8685 | 0.06 | 10000 | 0.8540 | 0.7341 | |
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| 0.8422 | 0.07 | 12000 | 0.8547 | 0.7365 | |
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| 0.8535 | 0.08 | 14000 | 0.8264 | 0.7372 | |
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| 0.8178 | 0.09 | 16000 | 0.8331 | 0.7389 | |
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| 0.8325 | 0.1 | 18000 | 0.8242 | 0.7411 | |
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| 0.8181 | 0.12 | 20000 | 0.8356 | 0.7437 | |
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| 0.8171 | 0.13 | 22000 | 0.8090 | 0.7451 | |
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| 0.8092 | 0.14 | 24000 | 0.8469 | 0.7392 | |
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| 0.8057 | 0.15 | 26000 | 0.8185 | 0.7478 | |
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| 0.8085 | 0.16 | 28000 | 0.8090 | 0.7467 | |
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| 0.8229 | 0.17 | 30000 | 0.8225 | 0.7417 | |
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| 0.8151 | 0.18 | 32000 | 0.8262 | 0.7419 | |
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| 0.81 | 0.2 | 34000 | 0.8149 | 0.7383 | |
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| 0.8073 | 0.21 | 36000 | 0.8225 | 0.7441 | |
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| 0.816 | 0.22 | 38000 | 0.8037 | 0.744 | |
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| 0.8217 | 0.23 | 40000 | 0.8409 | 0.743 | |
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| 0.82 | 0.24 | 42000 | 0.8286 | 0.7385 | |
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| 0.8101 | 0.25 | 44000 | 0.8282 | 0.7413 | |
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| 0.8254 | 0.27 | 46000 | 0.8170 | 0.7414 | |
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### Framework versions |
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- Transformers 4.10.2 |
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- Pytorch 1.7.1 |
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- Datasets 1.6.1 |
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- Tokenizers 0.10.3 |
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