transformers tensorboard safetensors distilbert text-classification generated_from_trainer base_model:gc394/da_distilbert base_model:finetune:gc394/da_distilbert license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
base_model: gc394/da_distilbert
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: ft_da_distilbert_cpi
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ft_da_distilbert_cpi

This model is a fine-tuned version of [gc394/da_distilbert](https://huggingface.co/gc394/da_distilbert) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Mape: 2.0758
- Rmse: 0.0048

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mape   | Rmse   |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| No log        | 1.0   | 105  | 0.0001          | 3.3966 | 0.0073 |
| No log        | 2.0   | 210  | 0.0000          | 2.7221 | 0.0055 |
| No log        | 3.0   | 315  | 0.0000          | 5.1021 | 0.0063 |
| No log        | 4.0   | 420  | 0.0000          | 3.3576 | 0.0053 |
| 0.0004        | 5.0   | 525  | 0.0000          | 2.0579 | 0.0050 |
| 0.0004        | 6.0   | 630  | 0.0000          | 3.7841 | 0.0053 |
| 0.0004        | 7.0   | 735  | 0.0000          | 2.3032 | 0.0049 |
| 0.0004        | 8.0   | 840  | 0.0000          | 3.3604 | 0.0050 |
| 0.0004        | 9.0   | 945  | 0.0000          | 2.0758 | 0.0048 |
| 0.0001        | 10.0  | 1050 | 0.0000          | 1.9946 | 0.0048 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.4.0.dev20240502
- Datasets 2.19.0
- Tokenizers 0.19.1
