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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: distilbert-tweet_eval-emotion |
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results: [] |
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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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# distilbert-tweet_eval-emotion |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the tweet_eval dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2519 |
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- Accuracy: 0.9212 |
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- Precision: 0.9333 |
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- Recall: 0.7424 |
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- F1: 0.8138 |
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- Auroc: 0.9510 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- training_steps: 1000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Auroc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:| |
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| 0.4845 | 2.5 | 250 | 0.4243 | 0.8061 | 0.2000 | 0.0500 | 0.0800 | 0.9209 | |
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| 0.2692 | 5.0 | 500 | 0.2946 | 0.9151 | 0.9333 | 0.7091 | 0.7871 | 0.9469 | |
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| 0.192 | 7.5 | 750 | 0.2599 | 0.9151 | 0.9333 | 0.7091 | 0.7871 | 0.9500 | |
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| 0.1502 | 10.0 | 1000 | 0.2519 | 0.9212 | 0.9333 | 0.7424 | 0.8138 | 0.9510 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.1 |
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