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---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
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: 0.1759
- Accuracy: 0.94
- F1: 0.9401
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.798 | 1.0 | 250 | 0.2630 | 0.9155 | 0.9160 |
| 0.1996 | 2.0 | 500 | 0.1630 | 0.9345 | 0.9345 |
| 0.1324 | 3.0 | 750 | 0.1518 | 0.9385 | 0.9393 |
| 0.1033 | 4.0 | 1000 | 0.1475 | 0.9385 | 0.9385 |
| 0.0858 | 5.0 | 1250 | 0.1434 | 0.942 | 0.9416 |
| 0.0703 | 6.0 | 1500 | 0.1568 | 0.942 | 0.9422 |
| 0.0592 | 7.0 | 1750 | 0.1676 | 0.938 | 0.9380 |
| 0.0499 | 8.0 | 2000 | 0.1693 | 0.936 | 0.9364 |
| 0.0399 | 9.0 | 2250 | 0.1759 | 0.937 | 0.9373 |
| 0.0366 | 10.0 | 2500 | 0.1759 | 0.94 | 0.9401 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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