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--- |
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license: apache-2.0 |
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base_model: bert-base-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: assignment2_meher_test3 |
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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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# assignment2_meher_test3 |
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5370 |
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- Precision: 0.1642 |
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- Recall: 0.4158 |
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- F1: 0.2354 |
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- Accuracy: 0.8892 |
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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: 8 |
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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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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 149 | 0.3231 | 0.1406 | 0.2405 | 0.1774 | 0.9098 | |
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| No log | 2.0 | 298 | 0.2897 | 0.1711 | 0.3505 | 0.2300 | 0.9103 | |
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| No log | 3.0 | 447 | 0.3376 | 0.1715 | 0.3849 | 0.2373 | 0.9029 | |
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| 0.3658 | 4.0 | 596 | 0.3870 | 0.1669 | 0.4261 | 0.2398 | 0.8887 | |
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| 0.3658 | 5.0 | 745 | 0.4245 | 0.1542 | 0.3952 | 0.2218 | 0.8884 | |
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| 0.3658 | 6.0 | 894 | 0.4291 | 0.1815 | 0.3986 | 0.2495 | 0.9024 | |
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| 0.0735 | 7.0 | 1043 | 0.5257 | 0.1530 | 0.4296 | 0.2256 | 0.8820 | |
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| 0.0735 | 8.0 | 1192 | 0.5211 | 0.1680 | 0.4261 | 0.2410 | 0.8900 | |
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| 0.0735 | 9.0 | 1341 | 0.5810 | 0.1560 | 0.4502 | 0.2317 | 0.8784 | |
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| 0.0735 | 10.0 | 1490 | 0.5370 | 0.1642 | 0.4158 | 0.2354 | 0.8892 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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