---
license: apache-2.0
base_model: distilbert/distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-v0
  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. -->

# distilbert-v0

This model is a fine-tuned version of [distilbert/distilbert-base-cased](https://huggingface.co/distilbert/distilbert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4249
- Precision: 0.0860
- Recall: 0.0883
- F1: 0.0792
- Accuracy: 0.1013

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 29   | 2.3644          | 0.0657    | 0.0917 | 0.0241 | 0.1193   |
| No log        | 2.0   | 58   | 2.3651          | 0.0979    | 0.0925 | 0.0338 | 0.1195   |
| No log        | 3.0   | 87   | 2.3686          | 0.0742    | 0.0923 | 0.0498 | 0.1148   |
| No log        | 4.0   | 116  | 2.3718          | 0.0904    | 0.0918 | 0.0619 | 0.1132   |
| No log        | 5.0   | 145  | 2.3800          | 0.0893    | 0.0913 | 0.0758 | 0.1082   |
| No log        | 6.0   | 174  | 2.3946          | 0.0873    | 0.0915 | 0.0772 | 0.1070   |
| No log        | 7.0   | 203  | 2.4064          | 0.0864    | 0.0897 | 0.0780 | 0.1043   |
| No log        | 8.0   | 232  | 2.4165          | 0.0872    | 0.0888 | 0.0798 | 0.1019   |
| No log        | 9.0   | 261  | 2.4233          | 0.0860    | 0.0885 | 0.0778 | 0.1024   |
| No log        | 10.0  | 290  | 2.4249          | 0.0860    | 0.0883 | 0.0792 | 0.1013   |


### Framework versions

- Transformers 4.36.1
- Pytorch 2.2.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0