---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: trainer10c
  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. -->

# trainer10c

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.8551
- Precision: 0.6429
- Recall: 0.5833
- F1: 0.5823
- Accuracy: 0.5833

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0001        | 0.57  | 30   | 2.6795          | 0.5960    | 0.5357 | 0.5408 | 0.5357   |
| 0.0608        | 1.13  | 60   | 2.5244          | 0.6958    | 0.6667 | 0.6658 | 0.6667   |
| 0.0022        | 1.7   | 90   | 3.1879          | 0.6149    | 0.5476 | 0.5234 | 0.5476   |
| 0.0001        | 2.26  | 120  | 3.5031          | 0.6994    | 0.6071 | 0.6155 | 0.6071   |
| 0.0018        | 2.83  | 150  | 3.4385          | 0.6736    | 0.5595 | 0.5684 | 0.5595   |
| 0.0013        | 3.4   | 180  | 3.9040          | 0.6345    | 0.5476 | 0.5422 | 0.5476   |
| 0.0           | 3.96  | 210  | 3.8575          | 0.6429    | 0.5833 | 0.5823 | 0.5833   |
| 0.0           | 4.53  | 240  | 3.8583          | 0.6429    | 0.5833 | 0.5823 | 0.5833   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2