jonastokoliu
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update model card README.md
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README.md
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@@ -24,16 +24,16 @@ model-index:
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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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@@ -41,13 +41,13 @@ should probably proofread and complete it, then remove this comment. -->
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# token_classification_finetune
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This model is a fine-tuned version of [
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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: 0.5759878419452887
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- name: Recall
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type: recall
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value: 0.35125115848007415
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- name: F1
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type: f1
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value: 0.436384571099597
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- name: Accuracy
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type: accuracy
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value: 0.9444206926036768
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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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# token_classification_finetune
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This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the wnut_17 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2489
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- Precision: 0.5760
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- Recall: 0.3513
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- F1: 0.4364
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- Accuracy: 0.9444
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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 | 0.2573 | 0.6011 | 0.3003 | 0.4005 | 0.9409 |
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| No log | 2.0 | 214 | 0.2489 | 0.5760 | 0.3513 | 0.4364 | 0.9444 |
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### Framework versions
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