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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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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: bert-finetuned-comp2
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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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# bert-finetuned-comp2
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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: 0.9570
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- Precision: 0.5169
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- Recall: 0.6765
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- F1: 0.5820
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- Accuracy: 0.5820
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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: 1
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 8
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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: 7
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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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| 0.8434 | 1.0 | 934 | 0.7147 | 0.4475 | 0.6252 | 0.5096 | 0.5096 |
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| 0.6307 | 2.0 | 1868 | 0.5959 | 0.5058 | 0.6536 | 0.5585 | 0.5585 |
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| 0.4691 | 3.0 | 2802 | 0.6555 | 0.4761 | 0.6865 | 0.5521 | 0.5521 |
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| 0.334 | 4.0 | 3736 | 0.7211 | 0.5292 | 0.6682 | 0.5863 | 0.5863 |
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| 0.2326 | 5.0 | 4670 | 0.8046 | 0.4886 | 0.6865 | 0.5682 | 0.5682 |
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| 0.1625 | 6.0 | 5604 | 0.8650 | 0.4972 | 0.6851 | 0.5728 | 0.5728 |
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| 0.1195 | 7.0 | 6538 | 0.9570 | 0.5169 | 0.6765 | 0.5820 | 0.5820 |
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 1.10.0+cu111
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- Datasets 2.0.0
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- Tokenizers 0.11.6
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