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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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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: DistilBERT-finetuned-ner-S800 |
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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-finetuned-ner-S800 |
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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: 0.0834 |
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- Precision: 0.5329 |
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- Recall: 0.6129 |
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- F1: 0.5701 |
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- Accuracy: 0.9689 |
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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: 8 |
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- eval_batch_size: 8 |
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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 | 55 | 0.1363 | 0.2460 | 0.2987 | 0.2698 | 0.9436 | |
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| No log | 2.0 | 110 | 0.0926 | 0.3943 | 0.4656 | 0.4270 | 0.9636 | |
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| No log | 3.0 | 165 | 0.0823 | 0.4937 | 0.6059 | 0.5441 | 0.9683 | |
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| No log | 4.0 | 220 | 0.0802 | 0.5187 | 0.5849 | 0.5498 | 0.9696 | |
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| No log | 5.0 | 275 | 0.0834 | 0.5329 | 0.6129 | 0.5701 | 0.9689 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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