Trained on custom dataset

README.md

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+---
+library_name: transformers
+license: mit
+base_model: FacebookAI/roberta-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: FacebookAI_roberta-large_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-large_custom_data
+
+This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3779
+- Precision Macro: 0.8141
+- Recall Macro: 0.8170
+- F1 Macro: 0.8155
+- Accuracy: 0.8117
+
+## 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 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------:|:--------:|:--------:|
+| 0.5113        | 1.0   | 270  | 0.3779          | 0.8141          | 0.8170       | 0.8155   | 0.8117   |
+| 0.3962        | 2.0   | 540  | 0.4214          | 0.8266          | 0.8093       | 0.8125   | 0.8200   |
+| 0.2556        | 3.0   | 810  | 0.4619          | 0.8149          | 0.8106       | 0.8112   | 0.8135   |
+
+
+### Framework versions
+
+- Transformers 4.48.0
+- Pytorch 2.5.1
+- Datasets 3.2.0
+- Tokenizers 0.21.0

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