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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: vinai/phobert-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: phobert-human-tl-seg-seed-42
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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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+ # phobert-human-tl-seg-seed-42
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+
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+ This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4484
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+ - Accuracy: 0.8428
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+ - Precision: 0.6491
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+ - Recall: 0.4691
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+ - F1: 0.4932
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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: 0.0001
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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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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+ - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 50
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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 | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | No log | 1.0 | 346 | 0.5133 | 0.8256 | 0.5419 | 0.3574 | 0.3465 |
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+ | 0.5919 | 2.0 | 692 | 0.4692 | 0.8372 | 0.6180 | 0.4317 | 0.4475 |
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+ | 0.4602 | 3.0 | 1038 | 0.4660 | 0.8361 | 0.6390 | 0.4132 | 0.4307 |
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+ | 0.4602 | 4.0 | 1384 | 0.4649 | 0.8394 | 0.6767 | 0.4268 | 0.4487 |
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+ | 0.4568 | 5.0 | 1730 | 0.4581 | 0.8372 | 0.6211 | 0.4259 | 0.4459 |
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+ | 0.4498 | 6.0 | 2076 | 0.4586 | 0.8402 | 0.6572 | 0.4411 | 0.4606 |
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+ | 0.4498 | 7.0 | 2422 | 0.4628 | 0.8372 | 0.6626 | 0.4118 | 0.4318 |
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+ | 0.4516 | 8.0 | 2768 | 0.4520 | 0.8417 | 0.6340 | 0.4522 | 0.4741 |
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+ | 0.4473 | 9.0 | 3114 | 0.4540 | 0.8387 | 0.6594 | 0.4217 | 0.4441 |
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+ | 0.4473 | 10.0 | 3460 | 0.4559 | 0.8447 | 0.6911 | 0.4675 | 0.4855 |
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+ | 0.451 | 11.0 | 3806 | 0.4530 | 0.8379 | 0.6461 | 0.4221 | 0.4468 |
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+ | 0.4436 | 12.0 | 4152 | 0.4484 | 0.8428 | 0.6491 | 0.4691 | 0.4932 |
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+ | 0.4436 | 13.0 | 4498 | 0.4499 | 0.8394 | 0.6503 | 0.4367 | 0.4648 |
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+ | 0.4506 | 14.0 | 4844 | 0.4526 | 0.8391 | 0.6419 | 0.4251 | 0.4486 |
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+ | 0.4418 | 15.0 | 5190 | 0.4523 | 0.8398 | 0.6584 | 0.4261 | 0.4522 |
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+ | 0.4497 | 16.0 | 5536 | 0.4667 | 0.8372 | 0.6662 | 0.4110 | 0.4317 |
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+ | 0.4497 | 17.0 | 5882 | 0.4474 | 0.8417 | 0.6431 | 0.4438 | 0.4686 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.51.1
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.5.0
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+ - Tokenizers 0.21.0
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