End of training

README.md

@@ -7,7 +7,6 @@ metrics:
 - precision
 - recall
 - f1
-- accuracy
 model-index:
 - name: fold_4
   results: []
@@ -16,15 +15,23 @@ model-index:
 <!-- 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. -->
 
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/amnasaeed100/FineTuning-ADE-change1/runs/94wgcdtp)
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+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/amnasaeed100/FineTuning-ADE-change1/runs/05nc4r5u)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/amnasaeed100/FineTuning-ADE-change1/runs/2tfkcyde)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/amnasaeed100/FineTuning-ADE-change1/runs/2zf1k4id)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/amnasaeed100/FineTuning-ADE-change1/runs/qyo3k3m3)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/amnasaeed100/FineTuning-ADE-change1/runs/hlahcpt7)
 # fold_4
 
 This model is a fine-tuned version of [Amna100/PreTraining-MLM](https://huggingface.co/Amna100/PreTraining-MLM) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0115
-- Precision: 0.7679
-- Recall: 0.7116
-- F1: 0.7387
-- Accuracy: 0.9972
+- Loss: 0.0095
+- Precision: 0.1834
+- Recall: 0.3042
+- F1: 0.5248
+- Pr Auc: 0.7701
+- Roc Auc: 0.9321
 
 ## Model description
 
@@ -43,26 +50,28 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
+- learning_rate: 5e-05
 - train_batch_size: 5
 - eval_batch_size: 5
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 3
+- num_epochs: 5
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.0287        | 1.0   | 636  | 0.0124          | 0.6534    | 0.5839 | 0.6167 | 0.9963   |
-| 0.01          | 2.0   | 1272 | 0.0115          | 0.7736    | 0.6383 | 0.6995 | 0.9968   |
-| 0.0062        | 3.0   | 1908 | 0.0115          | 0.7679    | 0.7116 | 0.7387 | 0.9972   |
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Pr Auc | Roc Auc |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:------:|:-------:|
+| 0.024         | 1.0   | 630  | 0.0081          | 0.3745    | 0.9507 | 0.7320 | 0.6332 | 0.9557  |
+| 0.0098        | 2.0   | 1260 | 0.0078          | 0.5987    | 0.1560 | 0.1560 | 0.6396 | 0.9464  |
+| 0.0059        | 3.0   | 1890 | 0.0084          | 0.0581    | 0.8662 | 0.6011 | 0.6335 | 0.9502  |
+| 0.0014        | 4.0   | 2520 | 0.0091          | 0.7081    | 0.0206 | 0.9699 | 0.7122 | 0.9370  |
+| 0.0005        | 5.0   | 3150 | 0.0095          | 0.8324    | 0.2123 | 0.1818 | 0.7701 | 0.9321  |
 
 
 ### Framework versions
 
-- Transformers 4.37.0.dev0
-- Pytorch 2.1.0+cu121
-- Datasets 2.16.1
-- Tokenizers 0.15.0
+- Transformers 4.41.0.dev0
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

config.json

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   "type_vocab_size": 0,
   "vocab_size": 50265
 }

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tokenizer.json

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