---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: original_model_fast_2
  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. -->

# original_model_fast_2

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: 1.5424
- Accuracy: 0.5282
- F1: 0.5311
- Precision: 0.5429
- Recall: 0.5280

## 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: 3e-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.3323        | 0.1566 | 500  | 0.8817          | 0.7273   | 0.7080 | 0.7290    | 0.7142 |
| 0.2778        | 0.3132 | 1000 | 0.8832          | 0.7286   | 0.7159 | 0.7264    | 0.7184 |
| 0.2965        | 0.4698 | 1500 | 0.8859          | 0.7242   | 0.7086 | 0.7216    | 0.7127 |
| 0.2977        | 0.6264 | 2000 | 0.8766          | 0.7247   | 0.7100 | 0.7236    | 0.7135 |
| 0.3062        | 0.7830 | 2500 | 0.8881          | 0.7242   | 0.7102 | 0.7246    | 0.7134 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1