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---
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license: mit
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base_model: FacebookAI/roberta-large
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tags:
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- generated_from_trainer
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model-index:
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- name: green_as_train_context_roberta-large_20e
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# green_as_train_context_roberta-large_20e
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This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.4371
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- Val Accuracy: 0.8913
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- Val Precision: 0.7554
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- Val Recall: 0.5910
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- Val F1: 0.6632
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-06
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 20
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Val Accuracy | Val Precision | Val Recall | Val F1 |
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|:-------------:|:-----:|:-----:|:---------------:|:------------:|:-------------:|:----------:|:------:|
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| 0.1908 | 1.0 | 1012 | 0.4035 | 0.8904 | 0.7844 | 0.5448 | 0.6430 |
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| 0.152 | 2.0 | 2024 | 0.4631 | 0.8930 | 0.7440 | 0.6235 | 0.6784 |
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| 0.12 | 3.0 | 3036 | 0.5046 | 0.8879 | 0.7028 | 0.6605 | 0.6810 |
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| 0.0757 | 4.0 | 4048 | 0.7762 | 0.8902 | 0.7438 | 0.6003 | 0.6644 |
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| 0.0557 | 5.0 | 5060 | 0.8961 | 0.8846 | 0.7273 | 0.5802 | 0.6455 |
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| 0.0319 | 6.0 | 6072 | 0.8864 | 0.8916 | 0.7338 | 0.6296 | 0.6777 |
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| 0.0235 | 7.0 | 7084 | 0.8025 | 0.8902 | 0.7348 | 0.6157 | 0.6700 |
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| 0.0125 | 8.0 | 8096 | 1.1034 | 0.8916 | 0.7559 | 0.5926 | 0.6644 |
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| 0.0114 | 9.0 | 9108 | 1.1414 | 0.8882 | 0.7422 | 0.5864 | 0.6552 |
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| 0.0147 | 10.0 | 10120 | 1.2555 | 0.8902 | 0.7401 | 0.6065 | 0.6667 |
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| 0.0068 | 11.0 | 11132 | 1.2923 | 0.8879 | 0.7526 | 0.5679 | 0.6473 |
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| 0.0112 | 12.0 | 12144 | 1.3150 | 0.8890 | 0.8024 | 0.5139 | 0.6265 |
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| 0.0059 | 13.0 | 13156 | 1.1883 | 0.8899 | 0.7396 | 0.6049 | 0.6655 |
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| 0.0056 | 14.0 | 14168 | 1.3822 | 0.8871 | 0.7824 | 0.5216 | 0.6259 |
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| 0.0029 | 15.0 | 15180 | 1.4309 | 0.8888 | 0.7741 | 0.5448 | 0.6395 |
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| 0.0021 | 16.0 | 16192 | 1.3541 | 0.8916 | 0.7529 | 0.5972 | 0.6661 |
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| 0.004 | 17.0 | 17204 | 1.3666 | 0.8907 | 0.7384 | 0.6142 | 0.6706 |
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| 0.0022 | 18.0 | 18216 | 1.4396 | 0.8896 | 0.7525 | 0.5818 | 0.6562 |
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| 0.0028 | 19.0 | 19228 | 1.4340 | 0.8910 | 0.7539 | 0.5910 | 0.6626 |
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| 0.0001 | 20.0 | 20240 | 1.4371 | 0.8913 | 0.7554 | 0.5910 | 0.6632 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.1.2
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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