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WzY1924561588
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distilbert-base-uncased-finetuned-emotion

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  1. README.md +8 -8
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -23,23 +23,23 @@ model-index:
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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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@@ -70,8 +70,8 @@ The following hyperparameters were used during training:
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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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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9285
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  - name: F1
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  type: f1
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+ value: 0.9286327520264782
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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/0l0zgyh5)
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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: 0.2044
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+ - Accuracy: 0.9285
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+ - F1: 0.9286
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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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+ | 0.8044 | 1.0 | 250 | 0.2926 | 0.912 | 0.9117 |
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+ | 0.2398 | 2.0 | 500 | 0.2044 | 0.9285 | 0.9286 |
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  ### Framework versions
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