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README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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datasets:
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- sentiment140
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metrics:
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- accuracy
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model-index:
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- name: Sentiment140_XLNET_5E
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: sentiment140
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type: sentiment140
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config: sentiment140
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split: train
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args: sentiment140
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.84
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# Sentiment140_XLNET_5E
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This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the sentiment140 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3797
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- Accuracy: 0.84
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 3e-05
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.6687 | 0.08 | 50 | 0.5194 | 0.76 |
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| 0.5754 | 0.16 | 100 | 0.4500 | 0.7867 |
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| 0.5338 | 0.24 | 150 | 0.3725 | 0.8333 |
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| 0.5065 | 0.32 | 200 | 0.4093 | 0.8133 |
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| 0.4552 | 0.4 | 250 | 0.3910 | 0.8267 |
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| 0.5352 | 0.48 | 300 | 0.3888 | 0.82 |
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| 0.415 | 0.56 | 350 | 0.3887 | 0.8267 |
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| 0.4716 | 0.64 | 400 | 0.3888 | 0.84 |
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| 0.4565 | 0.72 | 450 | 0.3619 | 0.84 |
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| 0.4447 | 0.8 | 500 | 0.3758 | 0.8333 |
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| 0.4407 | 0.88 | 550 | 0.3664 | 0.8133 |
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| 0.46 | 0.96 | 600 | 0.3797 | 0.84 |
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### Framework versions
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- Transformers 4.24.0
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- Pytorch 1.13.0
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- Datasets 2.3.2
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- Tokenizers 0.13.1
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