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Training completed!
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README.md
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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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should probably proofread and complete it, then remove this comment. -->
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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: 0.1618
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- Accuracy: 0.937
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- F1: 0.9370
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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: 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: 8
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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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| 0.7529 | 1.0 | 250 | 0.2673 | 0.918 | 0.9187 |
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| 0.1932 | 2.0 | 500 | 0.1696 | 0.9325 | 0.9322 |
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| 0.1291 | 3.0 | 750 | 0.1491 | 0.937 | 0.9375 |
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| 0.0996 | 4.0 | 1000 | 0.1465 | 0.937 | 0.9367 |
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| 0.0806 | 5.0 | 1250 | 0.1475 | 0.9385 | 0.9382 |
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| 0.0698 | 6.0 | 1500 | 0.1567 | 0.936 | 0.9360 |
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| 0.0595 | 7.0 | 1750 | 0.1611 | 0.934 | 0.9338 |
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| 0.0519 | 8.0 | 2000 | 0.1618 | 0.937 | 0.9370 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.5.0+cu121
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- Datasets 3.0.2
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- Tokenizers 0.19.1
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