End of training
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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 | 107 | 0.
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| No log | 2.0 | 214 | 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: 0.4609164420485175
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- name: Recall
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type: recall
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value: 0.15848007414272475
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- name: F1
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type: f1
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value: 0.23586206896551726
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- name: Accuracy
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type: accuracy
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value: 0.9349322388953016
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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: 0.3042
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- Precision: 0.4609
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- Recall: 0.1585
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- F1: 0.2359
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- Accuracy: 0.9349
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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 | 107 | 0.3166 | 0.1639 | 0.0093 | 0.0175 | 0.9275 |
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| No log | 2.0 | 214 | 0.3042 | 0.4609 | 0.1585 | 0.2359 | 0.9349 |
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### Framework versions
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