---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: finetuning-sentiment-model-distil-samples
  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. -->

# finetuning-sentiment-model-distil-samples

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3150
- Accuracy Percentage: 0.7514
- Accuracy Number: 133.0
- F1: 0.7460
- Precision: 0.7514
- Recall: 0.7514

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy Percentage | Accuracy Number | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:-------------------:|:---------------:|:------:|:---------:|:------:|
| 0.2349        | 1.0   | 22   | 0.6664          | 0.7571              | 134.0           | 0.7552 | 0.7571    | 0.7571 |
| 0.0531        | 2.0   | 44   | 1.0491          | 0.7232              | 128.0           | 0.7093 | 0.7232    | 0.7232 |
| 0.0374        | 3.0   | 66   | 1.1389          | 0.7119              | 126.0           | 0.7154 | 0.7119    | 0.7119 |
| 0.023         | 4.0   | 88   | 1.2514          | 0.7401              | 131.0           | 0.7288 | 0.7401    | 0.7401 |
| 0.0188        | 5.0   | 110  | 1.2064          | 0.7401              | 131.0           | 0.7355 | 0.7401    | 0.7401 |
| 0.0171        | 6.0   | 132  | 1.3531          | 0.7458              | 132.0           | 0.7365 | 0.7458    | 0.7458 |
| 0.0188        | 7.0   | 154  | 1.3221          | 0.7627              | 135.0           | 0.7534 | 0.7627    | 0.7627 |
| 0.0162        | 8.0   | 176  | 1.2874          | 0.7571              | 134.0           | 0.7507 | 0.7571    | 0.7571 |
| 0.018         | 9.0   | 198  | 1.2882          | 0.7627              | 135.0           | 0.7579 | 0.7627    | 0.7627 |
| 0.0097        | 10.0  | 220  | 1.3150          | 0.7514              | 133.0           | 0.7460 | 0.7514    | 0.7514 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3