---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- simplification
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: finetuned_sentiment_analysis_model_yelp
  results: []
---

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

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: 0.8819
- Precision: 0.6435
- Recall: 0.6438
- F1: 0.6435

## 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|
| 0.8693        | 1.0   | 3657  | 0.8631          | 0.6183    | 0.6197 | 0.6183 |
| 0.7493        | 2.0   | 7314  | 0.8451          | 0.6358    | 0.6361 | 0.6350 |
| 0.5914        | 3.0   | 10971 | 0.8819          | 0.6435    | 0.6438 | 0.6435 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1