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Training completed!
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README.md
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metrics:
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- name: Accuracy
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type: accuracy
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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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---
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/wzy_study/huggingface/runs/
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# distilbert-base-uncased-finetuned-emotion
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the emotion dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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- F1: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 0.
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### Framework versions
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- Transformers 4.42.3
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- Pytorch 2.
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9295
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- name: F1
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type: f1
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value: 0.9293429134768317
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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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+
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/wzy_study/huggingface/runs/8s6l1v80)
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# distilbert-base-uncased-finetuned-emotion
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the emotion dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2220
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- Accuracy: 0.9295
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- F1: 0.9293
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 0.8554 | 1.0 | 250 | 0.3277 | 0.909 | 0.9087 |
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| 0.258 | 2.0 | 500 | 0.2220 | 0.9295 | 0.9293 |
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### Framework versions
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- Transformers 4.42.3
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- Pytorch 2.2.2+cu118
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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