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--- |
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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: logs_rand |
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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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# logs_rand |
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- Loss: 0.0024 |
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- Precision: 0.8742 |
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- Recall: 0.8871 |
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- F1: 0.8806 |
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- Accuracy: 0.9992 |
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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: 64 |
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- eval_batch_size: 64 |
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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 | 57 | 0.0067 | 0.6685 | 0.6276 | 0.6474 | 0.9980 | |
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| No log | 2.0 | 114 | 0.0035 | 0.8286 | 0.8312 | 0.8299 | 0.9989 | |
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| No log | 3.0 | 171 | 0.0028 | 0.8690 | 0.8745 | 0.8717 | 0.9991 | |
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| No log | 4.0 | 228 | 0.0026 | 0.8693 | 0.8840 | 0.8766 | 0.9992 | |
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| No log | 5.0 | 285 | 0.0024 | 0.8742 | 0.8871 | 0.8806 | 0.9992 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.0.1 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
