---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: txsa-sentiment-distilbert-HPO-full
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# txsa-sentiment-distilbert-HPO-full

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: 0.2792
- Accuracy: 0.963
- F1: 0.963

## 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: 9.734765329618898e-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
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.8024        | 1.0   | 3211  | 0.3262          | 0.893    | 0.893  |
| 0.3227        | 2.0   | 6422  | 0.2226          | 0.947    | 0.9470 |
| 0.1723        | 3.0   | 9633  | 0.2092          | 0.956    | 0.956  |
| 0.0996        | 4.0   | 12844 | 0.2710          | 0.96     | 0.96   |
| 0.0621        | 5.0   | 16055 | 0.2792          | 0.963    | 0.963  |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2