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README.md

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+---
+license: mit
+base_model: FacebookAI/roberta-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- recall
+- f1
+model-index:
+- name: green_as_train_context_roberta-large
+  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. -->
+
+# green_as_train_context_roberta-large
+
+This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8427
+- Accuracy: 0.8885
+- Recall: 0.5802
+- F1: 0.6533
+
+## 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: 1e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
+| 0.1927        | 1.0   | 1012 | 0.3691          | 0.8916   | 0.5864 | 0.6620 |
+| 0.1417        | 2.0   | 2024 | 0.4204          | 0.8944   | 0.6281 | 0.6829 |
+| 0.0954        | 3.0   | 3036 | 0.5585          | 0.8932   | 0.6111 | 0.6746 |
+| 0.0447        | 4.0   | 4048 | 0.7888          | 0.8890   | 0.5849 | 0.6563 |
+| 0.0217        | 5.0   | 5060 | 0.8427          | 0.8885   | 0.5802 | 0.6533 |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2