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Training in progress, epoch 1

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README.md ADDED
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+ ---
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+ library_name: peft
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+ license: mit
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+ base_model: xlm-roberta-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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+ - f1
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+ model-index:
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+ - name: emotion-model11_0
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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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+ # emotion-model11_0
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+
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+ This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0583
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+ - Accuracy: 0.5828
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+ - F1: 0.5244
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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: 5e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 32
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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: 10
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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 | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | No log | 1.0 | 41 | 1.3349 | 0.3804 | 0.2096 |
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+ | 1.3438 | 2.0 | 82 | 1.2443 | 0.3804 | 0.2096 |
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+ | 1.2717 | 3.0 | 123 | 1.0583 | 0.5828 | 0.5244 |
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+ | 1.1723 | 4.0 | 164 | 1.0449 | 0.5215 | 0.3965 |
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+ | 1.1136 | 5.0 | 205 | 0.9935 | 0.5521 | 0.4423 |
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+ | 1.1136 | 6.0 | 246 | 0.9746 | 0.5890 | 0.5003 |
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+ | 1.1124 | 7.0 | 287 | 0.9637 | 0.5890 | 0.5003 |
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+ | 1.0842 | 8.0 | 328 | 0.9562 | 0.5767 | 0.4846 |
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+ | 1.0456 | 9.0 | 369 | 0.9516 | 0.5767 | 0.4837 |
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+ | 1.0552 | 10.0 | 410 | 0.9428 | 0.5767 | 0.4837 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.15.2
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+ - Transformers 4.52.4
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 3.6.0
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+ - Tokenizers 0.21.1
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