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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: BT5153-kaggle-sentiment-model-3000-samples
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. -->
# BT5153-kaggle-sentiment-model-3000-samples
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: 0.6160
- Accuracy: 0.9270
- F1: 0.9288
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.2851 | 1.0 | 625 | 0.2058 | 0.9216 | 0.9231 |
| 0.1735 | 2.0 | 1250 | 0.2257 | 0.9244 | 0.9258 |
| 0.121 | 3.0 | 1875 | 0.2907 | 0.9232 | 0.9251 |
| 0.0525 | 4.0 | 2500 | 0.3607 | 0.9194 | 0.9219 |
| 0.0381 | 5.0 | 3125 | 0.4109 | 0.9216 | 0.9233 |
| 0.0257 | 6.0 | 3750 | 0.4142 | 0.9232 | 0.9244 |
| 0.0192 | 7.0 | 4375 | 0.4321 | 0.9230 | 0.9233 |
| 0.0126 | 8.0 | 5000 | 0.4745 | 0.9250 | 0.9278 |
| 0.01 | 9.0 | 5625 | 0.5053 | 0.9240 | 0.9246 |
| 0.0091 | 10.0 | 6250 | 0.5256 | 0.9240 | 0.9267 |
| 0.0062 | 11.0 | 6875 | 0.5798 | 0.9246 | 0.9255 |
| 0.0033 | 12.0 | 7500 | 0.5935 | 0.9242 | 0.9262 |
| 0.0019 | 13.0 | 8125 | 0.5891 | 0.9286 | 0.9303 |
| 0.0018 | 14.0 | 8750 | 0.6176 | 0.9266 | 0.9287 |
| 0.0001 | 15.0 | 9375 | 0.6160 | 0.9270 | 0.9288 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2
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