End of training

README.md

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+---
+license: apache-2.0
+base_model: dandelin/vilt-b32-mlm
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- accuracy
+model-index:
+- name: vilt_finetuned_2
+  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. -->
+
+# vilt_finetuned_2
+
+This model is a fine-tuned version of [dandelin/vilt-b32-mlm](https://huggingface.co/dandelin/vilt-b32-mlm) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.3663
+- F1: 0.6000
+- Roc Auc: 0.7866
+- Accuracy: 0.5735
+
+## 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: 5e-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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
+| 44.1455       | 1.0   | 129  | 6.5479          | 0.1270 | 0.5367  | 0.0735   |
+| 2.9608        | 2.0   | 258  | 2.7634          | 0.4385 | 0.6965  | 0.3934   |
+| 2.3046        | 3.0   | 387  | 2.4919          | 0.4948 | 0.7204  | 0.4412   |
+| 1.895         | 4.0   | 516  | 2.3418          | 0.5652 | 0.7627  | 0.5257   |
+| 1.4785        | 5.0   | 645  | 2.6462          | 0.5720 | 0.7701  | 0.5404   |
+| 1.1491        | 6.0   | 774  | 2.8805          | 0.6074 | 0.7884  | 0.5772   |
+| 0.8297        | 7.0   | 903  | 3.1832          | 0.5977 | 0.7866  | 0.5735   |
+| 0.7249        | 8.0   | 1032 | 3.2679          | 0.6054 | 0.7903  | 0.5809   |
+| 2.1554        | 9.0   | 1161 | 3.2926          | 0.6119 | 0.7940  | 0.5846   |
+| 0.5323        | 10.0  | 1290 | 3.3663          | 0.6000 | 0.7866  | 0.5735   |
+
+
+### Framework versions
+
+- Transformers 4.40.0.dev0
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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