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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: txsa-sentiment-distilbert-HPO-full
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. -->
# txsa-sentiment-distilbert-HPO-full
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: 0.2792
- Accuracy: 0.963
- F1: 0.963
## 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: 9.734765329618898e-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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.8024 | 1.0 | 3211 | 0.3262 | 0.893 | 0.893 |
| 0.3227 | 2.0 | 6422 | 0.2226 | 0.947 | 0.9470 |
| 0.1723 | 3.0 | 9633 | 0.2092 | 0.956 | 0.956 |
| 0.0996 | 4.0 | 12844 | 0.2710 | 0.96 | 0.96 |
| 0.0621 | 5.0 | 16055 | 0.2792 | 0.963 | 0.963 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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