Training complete

README.md

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+---
+license: mit
+base_model: microsoft/biogpt
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: MLMA_biogpt_tuned_1412
+ 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. -->
+
+# MLMA_biogpt_tuned_1412
+
+This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1569
+- Precision: 0.4752
+- Recall: 0.5541
+- F1: 0.5116
+- Accuracy: 0.9544
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.3317 | 1.0 | 679 | 0.1753 | 0.3832 | 0.4923 | 0.4309 | 0.9436 |
+| 0.1765 | 2.0 | 1358 | 0.1625 | 0.4394 | 0.5531 | 0.4897 | 0.9496 |
+| 0.1057 | 3.0 | 2037 | 0.1569 | 0.4752 | 0.5541 | 0.5116 | 0.9544 |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2