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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-seed-69
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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-seed-69
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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: 0.4535
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+ - Accuracy: 0.8398
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+ - Precision: 0.6509
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+ - Recall: 0.4718
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+ - F1: 0.4965
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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 | 0.5169 | 0.8237 | 0.5413 | 0.3480 | 0.3291 |
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+ | 0.5883 | 2.0 | 692 | 0.4718 | 0.8320 | 0.6263 | 0.4068 | 0.4201 |
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+ | 0.4671 | 3.0 | 1038 | 0.4658 | 0.8335 | 0.6649 | 0.4074 | 0.4246 |
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+ | 0.4671 | 4.0 | 1384 | 0.4671 | 0.8368 | 0.6924 | 0.4163 | 0.4365 |
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+ | 0.4618 | 5.0 | 1730 | 0.4639 | 0.8357 | 0.6689 | 0.4144 | 0.4365 |
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+ | 0.4577 | 6.0 | 2076 | 0.4606 | 0.8357 | 0.6478 | 0.4245 | 0.4437 |
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+ | 0.4577 | 7.0 | 2422 | 0.4627 | 0.8357 | 0.6907 | 0.4133 | 0.4353 |
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+ | 0.4555 | 8.0 | 2768 | 0.4532 | 0.8394 | 0.6546 | 0.4429 | 0.4681 |
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+ | 0.4542 | 9.0 | 3114 | 0.4600 | 0.8338 | 0.6444 | 0.4071 | 0.4271 |
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+ | 0.4542 | 10.0 | 3460 | 0.4604 | 0.8342 | 0.6652 | 0.4372 | 0.4540 |
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+ | 0.4587 | 11.0 | 3806 | 0.4590 | 0.8357 | 0.6626 | 0.4125 | 0.4378 |
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+ | 0.4489 | 12.0 | 4152 | 0.4535 | 0.8398 | 0.6509 | 0.4718 | 0.4965 |
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+ | 0.4489 | 13.0 | 4498 | 0.4556 | 0.8353 | 0.6360 | 0.4202 | 0.4464 |
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+ | 0.4575 | 14.0 | 4844 | 0.4565 | 0.8361 | 0.6533 | 0.4141 | 0.4378 |
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+ | 0.449 | 15.0 | 5190 | 0.4597 | 0.8335 | 0.6578 | 0.4008 | 0.4203 |
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+ | 0.4588 | 16.0 | 5536 | 0.4663 | 0.8323 | 0.6494 | 0.3975 | 0.4143 |
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+ | 0.4588 | 17.0 | 5882 | 0.4515 | 0.8368 | 0.6142 | 0.4328 | 0.4568 |
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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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