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README.md
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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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datasets:
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- emotion
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metrics:
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- accuracy
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- f1
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model-index:
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- name: distilbert-base-uncased-finetuned-emotion
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: emotion
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type: emotion
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config: split
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split: validation
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args: split
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9215
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- name: F1
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type: f1
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value: 0.9214718883562769
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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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# distilbert-base-uncased-finetuned-emotion
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on
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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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### Framework versions
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- Transformers 4.
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- Pytorch 2.
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- Datasets 2.
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- Tokenizers 0.19.1
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---
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library_name: transformers
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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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- f1
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model-index:
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- name: distilbert-base-uncased-finetuned-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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# distilbert-base-uncased-finetuned-emotion
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2117
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- Accuracy: 0.9275
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- F1: 0.9275
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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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| 0.8106 | 1.0 | 250 | 0.3030 | 0.908 | 0.9064 |
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| 0.2435 | 2.0 | 500 | 0.2117 | 0.9275 | 0.9275 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.1.0+cu118
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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