---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: topic_classification
  results: []
---

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should probably proofread and complete it, then remove this comment. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/mlops-proj/my-amazing-project/runs/1di6dq34)
# topic_classification

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: 2.3890
- Model Preparation Time: 0.0033
- Accuracy: 0.15

## 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: 8
- eval_batch_size: 8
- 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
- training_steps: 30

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Model Preparation Time | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:----------------------:|:--------:|
| No log        | 0.3846 | 5    | 2.3190          | 0.0033                 | 0.15     |
| No log        | 0.7692 | 10   | 2.3612          | 0.0033                 | 0.15     |
| No log        | 1.1538 | 15   | 2.3687          | 0.0033                 | 0.15     |
| No log        | 1.5385 | 20   | 2.3841          | 0.0033                 | 0.15     |
| No log        | 1.9231 | 25   | 2.3890          | 0.0033                 | 0.15     |
| No log        | 2.3077 | 30   | 2.3890          | 0.0033                 | 0.15     |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0