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xlnet_classification

Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
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README.md ADDED
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+ ---
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+ library_name: transformers
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+ base_model: 5CD-AI/Vietnamese-Sentiment-visobert
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ model-index:
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+ - name: xlnet_classification
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+ results: []
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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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+ # xlnet_classification
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+
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+ This model is a fine-tuned version of [5CD-AI/Vietnamese-Sentiment-visobert](https://huggingface.co/5CD-AI/Vietnamese-Sentiment-visobert) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4639
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+ - F1: 0.9464
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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: 3e-05
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+ - train_batch_size: 128
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+ - eval_batch_size: 128
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 40.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | No log | 1.0 | 194 | 0.1743 | 0.9461 |
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+ | No log | 2.0 | 388 | 0.1837 | 0.9464 |
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+ | 0.1681 | 3.0 | 582 | 0.1892 | 0.9444 |
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+ | 0.1681 | 4.0 | 776 | 0.2257 | 0.9450 |
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+ | 0.1681 | 5.0 | 970 | 0.2677 | 0.9422 |
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+ | 0.0663 | 6.0 | 1164 | 0.2917 | 0.9369 |
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+ | 0.0663 | 7.0 | 1358 | 0.3442 | 0.9391 |
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+ | 0.0377 | 8.0 | 1552 | 0.3365 | 0.9417 |
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+ | 0.0377 | 9.0 | 1746 | 0.3301 | 0.9411 |
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+ | 0.0377 | 10.0 | 1940 | 0.3463 | 0.9428 |
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+ | 0.0259 | 11.0 | 2134 | 0.3746 | 0.9386 |
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+ | 0.0259 | 12.0 | 2328 | 0.4055 | 0.9436 |
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+ | 0.0173 | 13.0 | 2522 | 0.4070 | 0.9375 |
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+ | 0.0173 | 14.0 | 2716 | 0.4143 | 0.9419 |
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+ | 0.0173 | 15.0 | 2910 | 0.4322 | 0.9411 |
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+ | 0.014 | 16.0 | 3104 | 0.4182 | 0.9436 |
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+ | 0.014 | 17.0 | 3298 | 0.4002 | 0.9442 |
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+ | 0.014 | 18.0 | 3492 | 0.4194 | 0.9453 |
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+ | 0.0131 | 19.0 | 3686 | 0.4223 | 0.9439 |
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+ | 0.0131 | 20.0 | 3880 | 0.4358 | 0.9442 |
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+ | 0.0107 | 21.0 | 4074 | 0.4565 | 0.9411 |
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+ | 0.0107 | 22.0 | 4268 | 0.4561 | 0.9433 |
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+ | 0.0107 | 23.0 | 4462 | 0.4366 | 0.9453 |
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+ | 0.0094 | 24.0 | 4656 | 0.4435 | 0.9425 |
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+ | 0.0094 | 25.0 | 4850 | 0.4527 | 0.9461 |
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+ | 0.0091 | 26.0 | 5044 | 0.4759 | 0.9439 |
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+ | 0.0091 | 27.0 | 5238 | 0.4518 | 0.9464 |
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+ | 0.0091 | 28.0 | 5432 | 0.4447 | 0.9461 |
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+ | 0.0085 | 29.0 | 5626 | 0.4533 | 0.9456 |
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+ | 0.0085 | 30.0 | 5820 | 0.4549 | 0.9458 |
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+ | 0.0071 | 31.0 | 6014 | 0.4527 | 0.9470 |
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+ | 0.0071 | 32.0 | 6208 | 0.4533 | 0.9453 |
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+ | 0.0071 | 33.0 | 6402 | 0.4554 | 0.9481 |
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+ | 0.0072 | 34.0 | 6596 | 0.4629 | 0.9447 |
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+ | 0.0072 | 35.0 | 6790 | 0.4726 | 0.9450 |
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+ | 0.0072 | 36.0 | 6984 | 0.4511 | 0.9461 |
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+ | 0.0067 | 37.0 | 7178 | 0.4571 | 0.9447 |
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+ | 0.0067 | 38.0 | 7372 | 0.4676 | 0.9456 |
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+ | 0.0062 | 39.0 | 7566 | 0.4640 | 0.9461 |
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+ | 0.0062 | 40.0 | 7760 | 0.4639 | 0.9464 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.0.dev0
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 3.1.0
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+ - Tokenizers 0.21.0
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