---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuning-emotion-model-5-v2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# finetuning-emotion-model-5-v2

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1559
- Accuracy: 0.5885
- F1: 0.5876

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.9413        | 1.0   | 2250 | 0.9176          | 0.5816   | 0.5680 |
| 0.8226        | 2.0   | 4500 | 0.8871          | 0.6051   | 0.6027 |
| 0.6739        | 3.0   | 6750 | 0.9854          | 0.5969   | 0.5971 |
| 0.4879        | 4.0   | 9000 | 1.1559          | 0.5885   | 0.5876 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1