| --- |
| license: mit |
| tags: |
| - generated_from_trainer |
| datasets: |
| - sentiment140 |
| metrics: |
| - accuracy |
| model-index: |
| - name: Sentiment140_XLNET_5E |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: sentiment140 |
| type: sentiment140 |
| config: sentiment140 |
| split: train |
| args: sentiment140 |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.84 |
| --- |
| |
| <!-- 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. --> |
|
|
| # Sentiment140_XLNET_5E |
|
|
| This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the sentiment140 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3797 |
| - Accuracy: 0.84 |
|
|
| ## 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: 3e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 1 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.6687 | 0.08 | 50 | 0.5194 | 0.76 | |
| | 0.5754 | 0.16 | 100 | 0.4500 | 0.7867 | |
| | 0.5338 | 0.24 | 150 | 0.3725 | 0.8333 | |
| | 0.5065 | 0.32 | 200 | 0.4093 | 0.8133 | |
| | 0.4552 | 0.4 | 250 | 0.3910 | 0.8267 | |
| | 0.5352 | 0.48 | 300 | 0.3888 | 0.82 | |
| | 0.415 | 0.56 | 350 | 0.3887 | 0.8267 | |
| | 0.4716 | 0.64 | 400 | 0.3888 | 0.84 | |
| | 0.4565 | 0.72 | 450 | 0.3619 | 0.84 | |
| | 0.4447 | 0.8 | 500 | 0.3758 | 0.8333 | |
| | 0.4407 | 0.88 | 550 | 0.3664 | 0.8133 | |
| | 0.46 | 0.96 | 600 | 0.3797 | 0.84 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.24.0 |
| - Pytorch 1.13.0 |
| - Datasets 2.3.2 |
| - Tokenizers 0.13.1 |
|
|
