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-0.0001-32
+  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-0.0001-32
+
+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: 0.0835
+- Precision: 0.8178
+- Recall: 0.8281
+- F1: 0.8229
+- Accuracy: 0.9769
+
+## 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: 0.0001
+- 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  | 0.0882          | 0.7639    | 0.7805 | 0.7721 | 0.9718   |
+| No log        | 2.0   | 418  | 0.0735          | 0.8259    | 0.8222 | 0.8240 | 0.9775   |
+| 0.2568        | 3.0   | 627  | 0.0779          | 0.8060    | 0.8110 | 0.8085 | 0.9746   |
+| 0.2568        | 4.0   | 836  | 0.0815          | 0.8062    | 0.8245 | 0.8152 | 0.9768   |
+| 0.0375        | 5.0   | 1045 | 0.0835          | 0.8178    | 0.8281 | 0.8229 | 0.9769   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

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