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-0.0001-16
+  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-0.0001-16
+
+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: 0.0924
+- Precision: 0.8156
+- Recall: 0.8242
+- F1: 0.8199
+- Accuracy: 0.9768
+
+## 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: 16
+- eval_batch_size: 16
+- 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   | 417  | 0.0960          | 0.7712    | 0.8074 | 0.7889 | 0.9706   |
+| 0.3056        | 2.0   | 834  | 0.0765          | 0.8187    | 0.8211 | 0.8199 | 0.9766   |
+| 0.0587        | 3.0   | 1251 | 0.0784          | 0.8116    | 0.8104 | 0.8110 | 0.9744   |
+| 0.0401        | 4.0   | 1668 | 0.0877          | 0.8027    | 0.8316 | 0.8169 | 0.9758   |
+| 0.027         | 5.0   | 2085 | 0.0924          | 0.8156    | 0.8242 | 0.8199 | 0.9768   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

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