| --- |
| license: apache-2.0 |
| base_model: distilbert-base-uncased-finetuned-sst-2-english |
| tags: |
| - generated_from_trainer |
| datasets: |
| - glue |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: finetuning-SentimentAnalysis-model |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: glue |
| type: glue |
| config: sst2 |
| split: validation |
| args: sst2 |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9025229357798165 |
| - name: F1 |
| type: f1 |
| value: 0.9023551952126083 |
| --- |
| |
| <!-- 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-SentimentAnalysis-model |
|
|
| This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the glue dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3755 |
| - Accuracy: 0.9025 |
| - F1: 0.9024 |
|
|
| ## 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: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 2 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | 0.0575 | 1.0 | 1053 | 0.2953 | 0.9071 | 0.9070 | |
| | 0.0328 | 2.0 | 2106 | 0.3755 | 0.9025 | 0.9024 | |
|
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|
| ### Framework versions |
|
|
| - Transformers 4.31.0 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.3 |
| - Tokenizers 0.13.3 |
|
|
