---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: sentiment_pred_24feb
  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. -->

# sentiment_pred_24feb

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2754
- Y True: [1 1 1 0 1 1 0 1 0 1 0 1 1 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1 0 0 0 0 1 1 1 0 1
 1 1 1 1 1 0 0 1 1 1 0 1 1 1 1 1 1 1 1 0 1 1 1 0 1 1 1 0 0 1 1 1 0 0 0 1 0
 1 1 0 1 1 0 0 1 0 1 1 1 0 0 1 0 1 0 1 1 0 1 1 0 1 1 1 0 1 0 1 0 1 0 0 1 1
 1 1 1 1 1 0 1 1 0 0 0 1 1 1 0 1 0 1 0 1 0 0 1 1 1 1 0 0 1 0 1 1 1 0 1 1 1
 1 1 0 1 1 1 1 1 1 1 1 1 0 1 0 0 0 0 1 0 0 0 1 1 0 1 1 0 1 0 0 1 0 1 0 1 1
 1 1 0 1 0 1 1 0 0 0 1 1 1 0 1 0 0 0 1 1 0 1 1 0 1 1 1 1 1 1 1 0 0 1 0 1 1
 1 1 1 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
 0 0 0]
- Y Pred: [0 1 1 0 1 1 0 1 0 1 0 1 1 0 1 1 1 1 1 1 1 1 0 0 1 1 1 0 0 0 0 0 1 0 1 0 1
 1 1 0 1 1 1 0 1 1 1 0 1 1 0 1 1 0 1 1 0 1 1 1 0 1 1 1 0 0 1 1 1 0 0 0 1 0
 1 1 1 1 1 0 0 1 0 1 1 1 0 0 1 0 1 0 1 1 0 1 1 0 1 1 0 0 1 0 1 0 1 0 0 1 1
 1 1 1 1 1 0 1 1 0 0 0 0 0 0 0 1 0 1 0 1 0 0 1 1 1 1 0 0 1 0 1 1 1 0 1 1 1
 1 1 1 1 1 1 1 1 1 1 1 1 0 1 0 0 0 0 1 0 0 0 1 1 0 1 1 1 0 0 0 1 0 1 0 1 1
 1 1 0 1 0 1 1 0 0 1 0 1 1 0 1 0 0 0 0 1 0 1 1 0 1 1 1 1 1 1 1 0 0 1 0 1 0
 1 0 1 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
 0 0 0]
- Accuracy: 0.9298
- F1: 0.9297
- Precision: 0.9313
- Recall: 0.9298
- Confusion Matrix: [[145   6]
 [ 15 133]]

## 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_steps: 50
- num_epochs: 5

### Training results



### Framework versions

- Transformers 4.14.1
- Pytorch 1.13.1+cu117
- Datasets 1.16.1
- Tokenizers 0.10.3