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Sentiment140_ALBERT_5E

Text Classification
Transformers
PyTorch
albert
Generated from Trainer
Eval Results
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+ ---
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+ license: apache-2.0
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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_ALBERT_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: 0.8533333333333334
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+ ---
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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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+
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+ # Sentiment140_ALBERT_5E
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+
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+ This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the sentiment140 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6103
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+ - Accuracy: 0.8533
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-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: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.6713 | 0.08 | 50 | 0.5704 | 0.7333 |
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+ | 0.5742 | 0.16 | 100 | 0.4620 | 0.8 |
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+ | 0.5104 | 0.24 | 150 | 0.5536 | 0.74 |
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+ | 0.5313 | 0.32 | 200 | 0.5198 | 0.76 |
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+ | 0.5023 | 0.4 | 250 | 0.4286 | 0.8 |
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+ | 0.4871 | 0.48 | 300 | 0.4294 | 0.8267 |
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+ | 0.4513 | 0.56 | 350 | 0.4349 | 0.8133 |
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+ | 0.4647 | 0.64 | 400 | 0.4046 | 0.8333 |
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+ | 0.4827 | 0.72 | 450 | 0.4218 | 0.8333 |
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+ | 0.4517 | 0.8 | 500 | 0.4093 | 0.82 |
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+ | 0.4417 | 0.88 | 550 | 0.3999 | 0.84 |
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+ | 0.4701 | 0.96 | 600 | 0.3779 | 0.8867 |
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+ | 0.397 | 1.04 | 650 | 0.3730 | 0.8667 |
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+ | 0.3377 | 1.12 | 700 | 0.3833 | 0.8333 |
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+ | 0.411 | 1.2 | 750 | 0.3704 | 0.84 |
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+ | 0.3796 | 1.28 | 800 | 0.3472 | 0.86 |
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+ | 0.3523 | 1.36 | 850 | 0.3512 | 0.8733 |
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+ | 0.3992 | 1.44 | 900 | 0.3712 | 0.84 |
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+ | 0.3641 | 1.52 | 950 | 0.3718 | 0.82 |
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+ | 0.3973 | 1.6 | 1000 | 0.3508 | 0.84 |
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+ | 0.3576 | 1.68 | 1050 | 0.3600 | 0.86 |
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+ | 0.3701 | 1.76 | 1100 | 0.3287 | 0.8667 |
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+ | 0.3721 | 1.84 | 1150 | 0.3794 | 0.82 |
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+ | 0.3673 | 1.92 | 1200 | 0.3378 | 0.8733 |
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+ | 0.4223 | 2.0 | 1250 | 0.3508 | 0.86 |
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+ | 0.2745 | 2.08 | 1300 | 0.3835 | 0.86 |
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+ | 0.283 | 2.16 | 1350 | 0.3500 | 0.8533 |
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+ | 0.2769 | 2.24 | 1400 | 0.3334 | 0.8733 |
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+ | 0.2491 | 2.32 | 1450 | 0.3519 | 0.8867 |
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+ | 0.3237 | 2.4 | 1500 | 0.3438 | 0.86 |
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+ | 0.2662 | 2.48 | 1550 | 0.3513 | 0.8667 |
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+ | 0.2423 | 2.56 | 1600 | 0.3413 | 0.8867 |
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+ | 0.2655 | 2.64 | 1650 | 0.3126 | 0.8933 |
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+ | 0.2516 | 2.72 | 1700 | 0.3333 | 0.8733 |
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+ | 0.252 | 2.8 | 1750 | 0.3316 | 0.88 |
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+ | 0.2872 | 2.88 | 1800 | 0.3227 | 0.9 |
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+ | 0.306 | 2.96 | 1850 | 0.3383 | 0.8733 |
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+ | 0.248 | 3.04 | 1900 | 0.3474 | 0.8733 |
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+ | 0.1507 | 3.12 | 1950 | 0.4140 | 0.8667 |
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+ | 0.1994 | 3.2 | 2000 | 0.3729 | 0.8533 |
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+ | 0.167 | 3.28 | 2050 | 0.3782 | 0.8867 |
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+ | 0.1872 | 3.36 | 2100 | 0.4352 | 0.8867 |
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+ | 0.1611 | 3.44 | 2150 | 0.4511 | 0.8667 |
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+ | 0.2338 | 3.52 | 2200 | 0.4244 | 0.8533 |
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+ | 0.1538 | 3.6 | 2250 | 0.4226 | 0.8733 |
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+ | 0.1561 | 3.68 | 2300 | 0.4126 | 0.88 |
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+ | 0.2156 | 3.76 | 2350 | 0.4382 | 0.86 |
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+ | 0.1684 | 3.84 | 2400 | 0.4969 | 0.86 |
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+ | 0.1917 | 3.92 | 2450 | 0.4439 | 0.8667 |
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+ | 0.1584 | 4.0 | 2500 | 0.4759 | 0.86 |
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+ | 0.1038 | 4.08 | 2550 | 0.5042 | 0.8667 |
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+ | 0.0983 | 4.16 | 2600 | 0.5527 | 0.8533 |
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+ | 0.1404 | 4.24 | 2650 | 0.5801 | 0.84 |
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+ | 0.0844 | 4.32 | 2700 | 0.5884 | 0.86 |
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+ | 0.1347 | 4.4 | 2750 | 0.5865 | 0.8467 |
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+ | 0.1373 | 4.48 | 2800 | 0.5915 | 0.8533 |
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+ | 0.1506 | 4.56 | 2850 | 0.5976 | 0.8467 |
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+ | 0.1007 | 4.64 | 2900 | 0.6678 | 0.82 |
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+ | 0.1311 | 4.72 | 2950 | 0.6082 | 0.8533 |
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+ | 0.1402 | 4.8 | 3000 | 0.6180 | 0.8467 |
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+ | 0.1363 | 4.88 | 3050 | 0.6107 | 0.8533 |
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+ | 0.0995 | 4.96 | 3100 | 0.6103 | 0.8533 |
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+
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+
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+ ### Framework versions
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+
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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