Trained on custom dataset

README.md

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+---
+library_name: transformers
+license: mit
+base_model: FacebookAI/roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: FacebookAI_roberta-base_custom_data
+  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. -->
+
+# FacebookAI_roberta-base_custom_data
+
+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: 0.3682
+- Precision Macro: 0.8383
+- Recall Macro: 0.8140
+- F1 Macro: 0.8200
+- Accuracy: 0.8265
+
+## 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: 16
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision Macro | Recall Macro | F1 Macro | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------:|:--------:|:--------:|
+| 0.4598        | 1.0   | 270  | 0.4176          | 0.8068          | 0.8221       | 0.8125   | 0.8052   |
+| 0.3705        | 2.0   | 540  | 0.3682          | 0.8383          | 0.8140       | 0.8200   | 0.8265   |
+| 0.3           | 3.0   | 810  | 0.4171          | 0.8237          | 0.8122       | 0.8150   | 0.8182   |
+
+
+### Framework versions
+
+- Transformers 4.47.0.dev0
+- Pytorch 2.5.1+cu124
+- Datasets 3.0.1
+- Tokenizers 0.20.1

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