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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: non_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. -->
+
+# non_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: 0.1773
+- Accuracy: 0.9776
+- Recall: 0.6993
+- F1: 0.7021
+
+## 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     |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|
+| 0.0584        | 1.0   | 7739  | 0.0916          | 0.9725   | 0.6942 | 0.6562 |
+| 0.0451        | 2.0   | 15478 | 0.0905          | 0.9773   | 0.6700 | 0.6902 |
+| 0.0296        | 3.0   | 23217 | 0.1112          | 0.9775   | 0.6912 | 0.6986 |
+| 0.0141        | 4.0   | 30956 | 0.1487          | 0.9759   | 0.7366 | 0.6979 |
+| 0.0102        | 5.0   | 38695 | 0.1773          | 0.9776   | 0.6993 | 0.7021 |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2