---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: quote-model-delta
  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. -->

# quote-model-delta

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2186
- Precision: 0.8199
- Recall: 0.9167
- F1: 0.8656
- Accuracy: 0.9309

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3956        | 1.0   | 976  | 0.2257          | 0.8077    | 0.9181 | 0.8594 | 0.9280   |
| 0.184         | 2.0   | 1952 | 0.2180          | 0.8188    | 0.9212 | 0.8670 | 0.9303   |
| 0.1612        | 3.0   | 2928 | 0.2186          | 0.8199    | 0.9167 | 0.8656 | 0.9309   |


### Framework versions

- Transformers 4.30.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3