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

# training_with_callbacks

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1529
- Precision: 0.4993
- Recall: 0.5397
- F1: 0.5187
- Accuracy: 0.9661

## 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: 8
- eval_batch_size: 8
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 205  | 0.1641          | 0.3048    | 0.3556 | 0.3282 | 0.9556   |
| No log        | 2.0   | 410  | 0.1387          | 0.4741    | 0.4365 | 0.4545 | 0.9642   |
| 0.1943        | 3.0   | 615  | 0.1430          | 0.4690    | 0.4810 | 0.4749 | 0.9648   |
| 0.1943        | 4.0   | 820  | 0.1481          | 0.4993    | 0.5365 | 0.5172 | 0.9655   |
| 0.0496        | 5.0   | 1025 | 0.1529          | 0.4993    | 0.5397 | 0.5187 | 0.9661   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.0+cpu
- Datasets 2.18.0
- Tokenizers 0.15.2