File size: 1,892 Bytes
b022a6a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 |
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Sentiment-Analysis-on-Twitter-BCS
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-Analysis-on-Twitter-BCS
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: 0.1303
- Accuracy: 0.9615
- Precision: 0.7730
- Recall: 0.6384
- F1: 0.6993
- Roc Auc: 0.9701
## 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: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 0.211 | 1.0 | 1798 | 0.1622 | 0.9515 | 0.6769 | 0.5893 | 0.6301 | 0.9417 |
| 0.1369 | 2.0 | 3596 | 0.1568 | 0.9568 | 0.7009 | 0.6696 | 0.6849 | 0.9646 |
| 0.1118 | 3.0 | 5394 | 0.1303 | 0.9615 | 0.7730 | 0.6384 | 0.6993 | 0.9701 |
| 0.0887 | 4.0 | 7192 | 0.1532 | 0.9631 | 0.8011 | 0.6295 | 0.7050 | 0.9708 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3
|