---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- text_classification
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-Global_Intent
  results: []
datasets:
- SetFit/amazon_massive_intent_en-US
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-uncased-finetuned-Global_Intent

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: 0.4771
- Accuracy: 0.8879
- F1: 0.8879

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.6913        | 1.0   | 180  | 0.6445          | 0.8431   | 0.8367 |
| 0.4537        | 2.0   | 360  | 0.4791          | 0.8824   | 0.8798 |
| 0.2192        | 3.0   | 540  | 0.4941          | 0.8775   | 0.8753 |
| 0.1098        | 4.0   | 720  | 0.4912          | 0.8844   | 0.8826 |
| 0.0628        | 5.0   | 900  | 0.4771          | 0.8879   | 0.8879 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1