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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: my_awesome_model |
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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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# my_awesome_model |
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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: 1.4723 |
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- Accuracy: {'accuracy': 0.5292066259808196} |
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- Precision: {'precision': 0.5270248196529665} |
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- Recall: {'recall': 0.5128581630410899} |
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- F1: {'f1': 0.4836938691814141} |
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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: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------------------------:|:---------------------------------:|:-------------------------------:|:---------------------------:| |
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| 2.3362 | 1.0 | 1390 | 1.8634 | {'accuracy': 0.4119442022667829} | {'precision': 0.3707812573639524} | {'recall': 0.39448170731707316} | {'f1': 0.33817627082664936} | |
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| 1.5346 | 2.0 | 2780 | 1.4723 | {'accuracy': 0.5292066259808196} | {'precision': 0.5270248196529665} | {'recall': 0.5128581630410899} | {'f1': 0.4836938691814141} | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.2.1 |
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- Tokenizers 0.19.1 |
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