---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: multi_balanced_model
  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. -->

# multi_balanced_model

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: 0.1478
- Precision: 0.7360
- Recall: 0.8434
- F1: 0.7861
- Accuracy: 0.8974

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 48   | 0.1606          | 0.6667    | 0.7829 | 0.7201 | 0.8609   |
| No log        | 2.0   | 96   | 0.1518          | 0.6646    | 0.7758 | 0.7159 | 0.8574   |
| No log        | 3.0   | 144  | 0.1535          | 0.6152    | 0.7509 | 0.6763 | 0.8417   |
| No log        | 4.0   | 192  | 0.1510          | 0.6747    | 0.7972 | 0.7308 | 0.8626   |
| No log        | 5.0   | 240  | 0.1562          | 0.7547    | 0.8541 | 0.8013 | 0.9061   |
| No log        | 6.0   | 288  | 0.1436          | 0.7205    | 0.8256 | 0.7695 | 0.8974   |
| No log        | 7.0   | 336  | 0.1466          | 0.7484    | 0.8363 | 0.7899 | 0.9026   |
| No log        | 8.0   | 384  | 0.1450          | 0.7690    | 0.8648 | 0.8141 | 0.9130   |
| No log        | 9.0   | 432  | 0.1474          | 0.7453    | 0.8541 | 0.7960 | 0.9043   |
| No log        | 10.0  | 480  | 0.1478          | 0.7360    | 0.8434 | 0.7861 | 0.8974   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2