End of training

README.md

@@ -0,0 +1,67 @@
+---
+license: mit
+tags:
+- generated_from_trainer
+model-index:
+- name: testing_img_token
+  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. -->
+
+# testing_img_token
+
+This model is a fine-tuned version of [SCUT-DLVCLab/lilt-roberta-en-base](https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9187
+- Eading: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2}
+- Ext: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9}
+- Ub heading: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15}
+- Overall Precision: 0.0
+- Overall Recall: 0.0
+- Overall F1: 0.0
+- Overall Accuracy: 0.4848
+
+## 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: 0.0005
+- 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
+- training_steps: 50
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Eading                                                    | Ext                                                       | Ub heading                                                 | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:----------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 1.4635        | 1.43  | 10   | 1.2178          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15} | 0.0               | 0.0            | 0.0        | 0.4848           |
+| 1.2206        | 2.86  | 20   | 1.0016          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15} | 0.0               | 0.0            | 0.0        | 0.4848           |
+| 1.0569        | 4.29  | 30   | 0.9783          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15} | 0.0               | 0.0            | 0.0        | 0.4848           |
+| 1.0201        | 5.71  | 40   | 0.9273          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15} | 0.0               | 0.0            | 0.0        | 0.4848           |
+| 0.9888        | 7.14  | 50   | 0.9187          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15} | 0.0               | 0.0            | 0.0        | 0.4848           |
+
+
+### Framework versions
+
+- Transformers 4.26.1
+- Pytorch 2.0.0+cu118
+- Datasets 2.11.0
+- Tokenizers 0.13.2

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preprocessor_config.json

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