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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results: []
---
<!-- 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. -->
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2905
- Accuracy: 0.896
- F1 Score: 0.8962
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 1.5116 | 1.0 | 250 | 1.2809 | 0.5315 | 0.4734 |
| 0.8731 | 2.0 | 500 | 0.5533 | 0.834 | 0.8273 |
| 0.4323 | 3.0 | 750 | 0.3940 | 0.863 | 0.8623 |
| 0.2737 | 4.0 | 1000 | 0.3179 | 0.89 | 0.8900 |
| 0.2098 | 5.0 | 1250 | 0.2963 | 0.8935 | 0.8932 |
| 0.1734 | 6.0 | 1500 | 0.2905 | 0.896 | 0.8962 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1
|