End of training

README.md

@@ -0,0 +1,80 @@
+---
+base_model: Rostlab/prot_bert
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: prot_bert-fine-tuned-toxicity_3
+  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
+
+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: 1.0450
+- Accuracy: 0.7419
+- Precision: 0.7530
+- Recall: 0.7419
+- F1: 0.7340
+
+## 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: 15
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.5735        | 1.0   | 16   | 0.5968          | 0.8065   | 0.8093    | 0.8065 | 0.8044 |
+| 0.4855        | 2.0   | 32   | 0.4939          | 0.8387   | 0.8391    | 0.8387 | 0.8380 |
+| 0.3499        | 3.0   | 48   | 0.5234          | 0.8065   | 0.8093    | 0.8065 | 0.8044 |
+| 0.3094        | 4.0   | 64   | 0.4639          | 0.8387   | 0.8391    | 0.8387 | 0.8380 |
+| 0.235         | 5.0   | 80   | 0.5654          | 0.8387   | 0.8391    | 0.8387 | 0.8380 |
+| 0.1608        | 6.0   | 96   | 0.6409          | 0.8387   | 0.8391    | 0.8387 | 0.8380 |
+| 0.1147        | 7.0   | 112  | 0.6271          | 0.8387   | 0.8391    | 0.8387 | 0.8380 |
+| 0.171         | 8.0   | 128  | 0.7704          | 0.8065   | 0.8093    | 0.8065 | 0.8044 |
+| 0.1762        | 9.0   | 144  | 0.7978          | 0.8065   | 0.8093    | 0.8065 | 0.8044 |
+| 0.1438        | 10.0  | 160  | 0.9561          | 0.7419   | 0.7530    | 0.7419 | 0.7340 |
+| 0.0953        | 11.0  | 176  | 1.0074          | 0.7419   | 0.7530    | 0.7419 | 0.7340 |
+| 0.0394        | 12.0  | 192  | 1.0037          | 0.7419   | 0.7530    | 0.7419 | 0.7340 |
+| 0.0896        | 13.0  | 208  | 1.0128          | 0.7419   | 0.7530    | 0.7419 | 0.7340 |
+| 0.0849        | 14.0  | 224  | 1.0404          | 0.7419   | 0.7530    | 0.7419 | 0.7340 |
+| 0.0207        | 15.0  | 240  | 1.0450          | 0.7419   | 0.7530    | 0.7419 | 0.7340 |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:878ac4783b45c5b5453238a69381ef6e0ce29d502290aff553c1f2bba2fb4305
+oid sha256:2110148c4ba9fcd75c7e6ca384151f536d75f942fedfab633ca867beb5bb2ad3
 size 1686085368