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_2.0.1
+  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_2.0.1
+
+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: 0.4239
+- Accuracy: 0.8387
+- Precision: 0.8391
+- Recall: 0.8387
+- F1: 0.8380
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.6945        | 1.0   | 16   | 0.6730          | 0.7742   | 0.8401    | 0.7742 | 0.7558 |
+| 0.6185        | 2.0   | 32   | 0.6087          | 0.8065   | 0.8093    | 0.8065 | 0.8044 |
+| 0.5241        | 3.0   | 48   | 0.5501          | 0.8387   | 0.8391    | 0.8387 | 0.8380 |
+| 0.466         | 4.0   | 64   | 0.5328          | 0.8387   | 0.8391    | 0.8387 | 0.8380 |
+| 0.4281        | 5.0   | 80   | 0.6886          | 0.7097   | 0.7252    | 0.7097 | 0.6967 |
+| 0.3393        | 6.0   | 96   | 0.4568          | 0.8387   | 0.8391    | 0.8387 | 0.8380 |
+| 0.1909        | 7.0   | 112  | 0.4239          | 0.8387   | 0.8391    | 0.8387 | 0.8380 |
+| 0.243         | 8.0   | 128  | 0.4323          | 0.8387   | 0.8391    | 0.8387 | 0.8380 |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

model.safetensors

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