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---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased-finetuned-sst-2-english
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-analysis-model-team-28
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. -->
# finetuning-sentiment-analysis-model-team-28
This model is a fine-tuned version of [distilbert/distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6973
- Accuracy: 0.9114
- F1: 0.9427
## 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: 1e-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: 500
- num_epochs: 6
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.021 | 1.0 | 175 | 0.5527 | 0.8986 | 0.9354 |
| 0.0123 | 2.0 | 350 | 0.5993 | 0.9029 | 0.9355 |
| 0.0002 | 3.0 | 525 | 0.7007 | 0.9029 | 0.9382 |
| 0.0313 | 4.0 | 700 | 0.6765 | 0.9086 | 0.9407 |
| 0.023 | 5.0 | 875 | 0.6983 | 0.9086 | 0.9405 |
| 0.0057 | 6.0 | 1050 | 0.6973 | 0.9114 | 0.9427 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.15.2
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