End of training

README.md

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+---
+license: mit
+base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract
+tags:
+- generated_from_trainer
+metrics:
+- f1
+model-index:
+- name: BiomedNLP-CIViC-evidence-level-finetuned
+  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. -->
+
+# BiomedNLP-CIViC-evidence-level-finetuned
+
+This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.5745
+- F1: 0.8312
+
+## 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: 2e-05
+- 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
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| No log        | 1.0   | 73   | 1.5464          | 0.8260 |
+| No log        | 2.0   | 146  | 1.7265          | 0.7844 |
+| No log        | 3.0   | 219  | 1.6166          | 0.8260 |
+| No log        | 4.0   | 292  | 1.5619          | 0.8260 |
+| No log        | 5.0   | 365  | 1.5745          | 0.8312 |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.2
+- Datasets 2.21.0
+- Tokenizers 0.15.0