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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: 0.1618
- Accuracy: 0.937
- F1: 0.9370
## 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: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.7529 | 1.0 | 250 | 0.2673 | 0.918 | 0.9187 |
| 0.1932 | 2.0 | 500 | 0.1696 | 0.9325 | 0.9322 |
| 0.1291 | 3.0 | 750 | 0.1491 | 0.937 | 0.9375 |
| 0.0996 | 4.0 | 1000 | 0.1465 | 0.937 | 0.9367 |
| 0.0806 | 5.0 | 1250 | 0.1475 | 0.9385 | 0.9382 |
| 0.0698 | 6.0 | 1500 | 0.1567 | 0.936 | 0.9360 |
| 0.0595 | 7.0 | 1750 | 0.1611 | 0.934 | 0.9338 |
| 0.0519 | 8.0 | 2000 | 0.1618 | 0.937 | 0.9370 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1
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