End of training

README.md

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+---
+base_model: Rostlab/prot_bert
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: prot_bert-fine-tuned-toxicity_3.1
+  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. -->
+
+# prot_bert-fine-tuned-toxicity_3.1
+
+This model is a fine-tuned version of [Rostlab/prot_bert](https://huggingface.co/Rostlab/prot_bert) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6981
+- Accuracy: 0.5484
+- Precision: 0.3007
+- Recall: 0.5484
+- F1: 0.3884
+
+## 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: 8
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.6948        | 1.0   | 16   | 0.6957          | 0.5484   | 0.3007    | 0.5484 | 0.3884 |
+| 0.6957        | 2.0   | 32   | 0.6965          | 0.5484   | 0.3007    | 0.5484 | 0.3884 |
+| 0.6939        | 3.0   | 48   | 0.6989          | 0.5484   | 0.3007    | 0.5484 | 0.3884 |
+| 0.6924        | 4.0   | 64   | 0.6977          | 0.5484   | 0.3007    | 0.5484 | 0.3884 |
+| 0.6924        | 5.0   | 80   | 0.6976          | 0.5484   | 0.3007    | 0.5484 | 0.3884 |
+| 0.6928        | 6.0   | 96   | 0.6984          | 0.5484   | 0.3007    | 0.5484 | 0.3884 |
+| 0.6923        | 7.0   | 112  | 0.6976          | 0.5484   | 0.3007    | 0.5484 | 0.3884 |
+| 0.6876        | 8.0   | 128  | 0.6981          | 0.5484   | 0.3007    | 0.5484 | 0.3884 |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1