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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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- f1 |
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model-index: |
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- name: distilbert-base-uncased_fold_3_binary_v1 |
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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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# distilbert-base-uncased_fold_3_binary_v1 |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9405 |
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- F1: 0.7878 |
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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: 25 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| No log | 1.0 | 289 | 0.4630 | 0.7897 | |
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| 0.3954 | 2.0 | 578 | 0.4549 | 0.7936 | |
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| 0.3954 | 3.0 | 867 | 0.6527 | 0.7868 | |
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| 0.1991 | 4.0 | 1156 | 0.7510 | 0.7951 | |
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| 0.1991 | 5.0 | 1445 | 0.9327 | 0.8000 | |
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| 0.095 | 6.0 | 1734 | 1.0974 | 0.7859 | |
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| 0.0347 | 7.0 | 2023 | 1.2692 | 0.7919 | |
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| 0.0347 | 8.0 | 2312 | 1.3718 | 0.7921 | |
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| 0.0105 | 9.0 | 2601 | 1.4679 | 0.7999 | |
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| 0.0105 | 10.0 | 2890 | 1.5033 | 0.8070 | |
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| 0.0079 | 11.0 | 3179 | 1.6074 | 0.8008 | |
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| 0.0079 | 12.0 | 3468 | 1.6921 | 0.7904 | |
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| 0.0053 | 13.0 | 3757 | 1.7079 | 0.7945 | |
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| 0.0054 | 14.0 | 4046 | 1.8361 | 0.7887 | |
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| 0.0054 | 15.0 | 4335 | 1.7695 | 0.7873 | |
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| 0.0046 | 16.0 | 4624 | 1.7934 | 0.7917 | |
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| 0.0046 | 17.0 | 4913 | 1.8036 | 0.8008 | |
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| 0.0064 | 18.0 | 5202 | 1.8780 | 0.7888 | |
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| 0.0064 | 19.0 | 5491 | 1.8943 | 0.7923 | |
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| 0.0032 | 20.0 | 5780 | 1.8694 | 0.7905 | |
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| 0.002 | 21.0 | 6069 | 1.9348 | 0.7869 | |
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| 0.002 | 22.0 | 6358 | 1.9578 | 0.7804 | |
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| 0.0036 | 23.0 | 6647 | 1.9438 | 0.7827 | |
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| 0.0036 | 24.0 | 6936 | 1.9386 | 0.7878 | |
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| 0.0011 | 25.0 | 7225 | 1.9405 | 0.7878 | |
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### Framework versions |
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- Transformers 4.21.0 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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