End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: FacebookAI/roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- accuracy
+model-index:
+- name: roberta-base-pr_tqacd
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# roberta-base-pr_tqacd
+
+This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.6056
+- F1 Macro: 0.5289
+- Precision: 0.5397
+- Recall: 0.5373
+- Accuracy: 0.7180
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 20
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1 Macro | Precision | Recall | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
+| No log        | 1.0   | 354  | 1.8365          | 0.3820   | 0.4312    | 0.4000 | 0.6106   |
+| 2.2658        | 2.0   | 708  | 1.3285          | 0.5013   | 0.5037    | 0.5722 | 0.6554   |
+| 1.5226        | 3.0   | 1062 | 1.2491          | 0.5450   | 0.5421    | 0.6006 | 0.7090   |
+| 1.5226        | 4.0   | 1416 | 1.3314          | 0.5476   | 0.5555    | 0.5767 | 0.7180   |
+| 1.1009        | 5.0   | 1770 | 1.4114          | 0.5468   | 0.5457    | 0.5754 | 0.7203   |
+| 0.7195        | 6.0   | 2124 | 1.6056          | 0.5289   | 0.5397    | 0.5373 | 0.7180   |
+
+
+### Framework versions
+
+- Transformers 4.57.1
+- Pytorch 2.8.0+cu128
+- Datasets 4.4.1
+- Tokenizers 0.22.1

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