Training complete

README.md

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+---
+library_name: transformers
+base_model: allenai/biomed_roberta_base
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: BioMedRoBERTa-finetuned-valid-testing-0.00005-32
+  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. -->
+
+# BioMedRoBERTa-finetuned-valid-testing-0.00005-32
+
+This model is a fine-tuned version of [allenai/biomed_roberta_base](https://huggingface.co/allenai/biomed_roberta_base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0815
+- Precision: 0.8113
+- Recall: 0.8227
+- F1: 0.8170
+- Accuracy: 0.9767
+
+## 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: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 209  | 0.1000          | 0.7636    | 0.7646 | 0.7641 | 0.9705   |
+| No log        | 2.0   | 418  | 0.0758          | 0.8278    | 0.8160 | 0.8219 | 0.9776   |
+| 0.2839        | 3.0   | 627  | 0.0788          | 0.7928    | 0.8070 | 0.7999 | 0.9745   |
+| 0.2839        | 4.0   | 836  | 0.0807          | 0.8028    | 0.8270 | 0.8148 | 0.9764   |
+| 0.0449        | 5.0   | 1045 | 0.0815          | 0.8113    | 0.8227 | 0.8170 | 0.9767   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

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