| ---
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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: finetuning-emotion-model
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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: 0.928
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| - name: F1
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| type: f1
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| value: 0.92794827672395
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| ---
|
|
|
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| should probably proofread and complete it, then remove this comment. -->
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|
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| # finetuning-emotion-model
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|
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| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/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: 0.2169
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| - Accuracy: 0.928
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| - F1: 0.9279
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|
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| ## Model description
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| More information needed
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|
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| ## Intended uses & limitations
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|
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| More information needed
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|
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| ## Training and evaluation data
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| More information needed
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|
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| ## Training procedure
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|
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| ### Training hyperparameters
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|
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| The following hyperparameters were used during training:
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| - learning_rate: 2e-05
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| - train_batch_size: 64
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| - eval_batch_size: 64
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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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| - num_epochs: 2
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|
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| ### Training results
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| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| | No log | 1.0 | 250 | 0.3225 | 0.902 | 0.9012 |
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| | 0.5453 | 2.0 | 500 | 0.2169 | 0.928 | 0.9279 |
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| ### Framework versions
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| - Transformers 4.42.4
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| - Pytorch 2.3.1+cu121
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| - Datasets 2.20.0
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| - Tokenizers 0.19.1
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|
