---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: distilbert-base-uncased
model-index:
- name: distilbert-base-uncased-finetuned-ft1500_reg2
  results: []
---

<!-- 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-ft1500_reg2

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: 0.7256
- Mse: 0.7256
- Mae: 0.6674
- R2: 0.4579
- Accuracy: 0.4573

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Mse    | Mae    | R2     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:--------:|
| 1.0689        | 1.0   | 3000  | 0.7823          | 0.7823 | 0.6948 | 0.4156 | 0.4327   |
| 0.6733        | 2.0   | 6000  | 0.7286          | 0.7286 | 0.6705 | 0.4556 | 0.4447   |
| 0.4735        | 3.0   | 9000  | 0.7125          | 0.7125 | 0.6658 | 0.4677 | 0.46     |
| 0.3358        | 4.0   | 12000 | 0.7256          | 0.7256 | 0.6674 | 0.4579 | 0.4573   |


### Framework versions

- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1