---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-analysis-model-team-28
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# finetuning-sentiment-analysis-model-team-28

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: 0.6302
- Accuracy: 0.7186
- F1: 0.8276

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.4621        | 1.0   | 175  | 0.5107          | 0.7843   | 0.8763 |
| 0.4787        | 2.0   | 350  | 0.6382          | 0.7743   | 0.8715 |
| 0.4371        | 3.0   | 525  | 0.6302          | 0.7186   | 0.8276 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.15.2