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--- |
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license: mit |
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base_model: roberta-large |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: roberta-large-finetuned_ADEs_SonatafyAI |
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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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# roberta-large-finetuned_ADEs_SonatafyAI |
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This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2571 |
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- Precision: 0.5269 |
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- Recall: 0.6208 |
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- F1: 0.5700 |
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- Accuracy: 0.8859 |
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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-07 |
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- train_batch_size: 8 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.7192 | 1.0 | 640 | 0.3366 | 0.4491 | 0.5202 | 0.4820 | 0.8653 | |
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| 0.3549 | 2.0 | 1280 | 0.2814 | 0.4982 | 0.6066 | 0.5471 | 0.8803 | |
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| 0.3118 | 3.0 | 1920 | 0.2653 | 0.5178 | 0.6186 | 0.5637 | 0.8831 | |
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| 0.2827 | 4.0 | 2560 | 0.2624 | 0.5276 | 0.6372 | 0.5772 | 0.8833 | |
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| 0.2741 | 5.0 | 3200 | 0.2571 | 0.5269 | 0.6208 | 0.5700 | 0.8859 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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