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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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metrics: |
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- accuracy |
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model-index: |
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- name: N_bert_sst5_padding80model |
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results: [] |
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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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# N_bert_sst5_padding80model |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.1055 |
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- Accuracy: 0.5335 |
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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: 20 |
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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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| 1.3295 | 1.0 | 534 | 1.2788 | 0.4231 | |
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| 1.0046 | 2.0 | 1068 | 1.1005 | 0.5362 | |
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| 0.7632 | 3.0 | 1602 | 1.1567 | 0.5357 | |
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| 0.588 | 4.0 | 2136 | 1.4030 | 0.5308 | |
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| 0.4198 | 5.0 | 2670 | 1.6242 | 0.5244 | |
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| 0.3036 | 6.0 | 3204 | 1.8412 | 0.5385 | |
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| 0.222 | 7.0 | 3738 | 2.2298 | 0.5299 | |
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| 0.1677 | 8.0 | 4272 | 2.4165 | 0.5376 | |
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| 0.1407 | 9.0 | 4806 | 2.7191 | 0.5285 | |
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| 0.1199 | 10.0 | 5340 | 3.1297 | 0.5226 | |
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| 0.0916 | 11.0 | 5874 | 3.3297 | 0.5466 | |
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| 0.0716 | 12.0 | 6408 | 3.4776 | 0.5385 | |
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| 0.0717 | 13.0 | 6942 | 3.6198 | 0.5339 | |
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| 0.047 | 14.0 | 7476 | 3.7826 | 0.5376 | |
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| 0.0322 | 15.0 | 8010 | 3.8744 | 0.5294 | |
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| 0.0268 | 16.0 | 8544 | 4.0318 | 0.5145 | |
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| 0.0204 | 17.0 | 9078 | 4.0118 | 0.5380 | |
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| 0.0201 | 18.0 | 9612 | 4.0902 | 0.5308 | |
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| 0.0149 | 19.0 | 10146 | 4.0749 | 0.5357 | |
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| 0.012 | 20.0 | 10680 | 4.1055 | 0.5335 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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