---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: trainer2
  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. -->

# trainer2

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: 2.9503
- Precision: 0.6569
- Recall: 0.6071
- F1: 0.6119
- Accuracy: 0.6071

## 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: 6e-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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0002        | 0.57  | 30   | 2.6229          | 0.6545    | 0.6071 | 0.6066 | 0.6071   |
| 0.0001        | 1.13  | 60   | 2.6791          | 0.6866    | 0.6310 | 0.6362 | 0.6310   |
| 0.0001        | 1.7   | 90   | 2.8369          | 0.6569    | 0.6071 | 0.6119 | 0.6071   |
| 0.0001        | 2.26  | 120  | 2.9043          | 0.6569    | 0.6071 | 0.6119 | 0.6071   |
| 0.0001        | 2.83  | 150  | 2.9231          | 0.6569    | 0.6071 | 0.6119 | 0.6071   |
| 0.0001        | 3.4   | 180  | 2.9291          | 0.6569    | 0.6071 | 0.6119 | 0.6071   |
| 0.0001        | 3.96  | 210  | 2.9367          | 0.6569    | 0.6071 | 0.6119 | 0.6071   |
| 0.0001        | 4.53  | 240  | 2.9472          | 0.6569    | 0.6071 | 0.6119 | 0.6071   |


### Framework versions

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