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README.md
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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-base-uncased_token_itr0_0.0001_all_01_03_2022-14_21_25
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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-base-uncased_token_itr0_0.0001_all_01_03_2022-14_21_25
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2698
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- Precision: 0.3321
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- Recall: 0.5265
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- F1: 0.4073
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- Accuracy: 0.8942
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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: 0.0001
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- train_batch_size: 32
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- eval_batch_size: 32
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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: 5
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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 | 30 | 0.3314 | 0.1627 | 0.3746 | 0.2269 | 0.8419 |
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| No log | 2.0 | 60 | 0.2957 | 0.2887 | 0.4841 | 0.3617 | 0.8592 |
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| No log | 3.0 | 90 | 0.2905 | 0.2429 | 0.5141 | 0.3299 | 0.8651 |
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| No log | 4.0 | 120 | 0.2759 | 0.3137 | 0.5565 | 0.4013 | 0.8787 |
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| No log | 5.0 | 150 | 0.2977 | 0.3116 | 0.5565 | 0.3995 | 0.8796 |
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### Framework versions
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- Transformers 4.15.0
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- Pytorch 1.10.1+cu113
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- Datasets 1.18.0
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- Tokenizers 0.10.3
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