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README.md
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metrics:
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- name: Precision
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type: precision
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value: 0.
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- name: Recall
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type: recall
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value: 0.
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- name: F1
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type: f1
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value: 0.
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- name: Accuracy
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type: accuracy
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value: 0.
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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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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the wnut_17 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Precision: 0.
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- Recall: 0.
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- F1: 0.
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- Accuracy: 0.
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## Model description
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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 | 213 | 0.
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| No log | 2.0 | 426 | 0.
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### Framework versions
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metrics:
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- name: Precision
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type: precision
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value: 0.5552523874488404
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- name: Recall
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type: recall
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value: 0.37720111214087115
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- name: F1
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type: f1
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value: 0.44922737306843263
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- name: Accuracy
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type: accuracy
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value: 0.9469454063528707
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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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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the wnut_17 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2942
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- Precision: 0.5553
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- Recall: 0.3772
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- F1: 0.4492
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- Accuracy: 0.9469
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## Model description
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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 | 213 | 0.2666 | 0.6024 | 0.2808 | 0.3831 | 0.9405 |
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| No log | 2.0 | 426 | 0.2605 | 0.5708 | 0.3364 | 0.4233 | 0.9456 |
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| 0.1299 | 3.0 | 639 | 0.2827 | 0.5658 | 0.3346 | 0.4205 | 0.9452 |
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| 0.1299 | 4.0 | 852 | 0.2836 | 0.5503 | 0.3753 | 0.4463 | 0.9469 |
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| 0.051 | 5.0 | 1065 | 0.2942 | 0.5553 | 0.3772 | 0.4492 | 0.9469 |
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### Framework versions
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