End of training
Browse files
README.md
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metrics:
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- name: Precision
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type: precision
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value: 0.
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- name: Recall
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type: recall
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value: 0.
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- name: F1
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type: f1
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value: 0.
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- name: Accuracy
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type: accuracy
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value: 0.
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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This model is a fine-tuned version of [layoutlmv3](https://huggingface.co/layoutlmv3) on the mp-02/cord-sroie dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Precision: 0.
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- Recall: 0.
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- F1: 0.
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- Accuracy: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| No log | 0.
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| No log | 1.
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| No log | 2.
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| No log |
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| 0.
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| 0.
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| 0.
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| 0.
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| 0.
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| 0.0995 | 7.9365 | 1000 | 0.0967 | 0.9037 | 0.9578 | 0.9300 | 0.9737 |
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| 0.0995 | 8.7302 | 1100 | 0.1224 | 0.8777 | 0.9642 | 0.9189 | 0.9690 |
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| 0.0995 | 9.5238 | 1200 | 0.1263 | 0.8879 | 0.9536 | 0.9196 | 0.9694 |
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### Framework versions
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metrics:
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- name: Precision
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type: precision
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value: 0.9129400570884871
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- name: Recall
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type: recall
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value: 0.9092632077706705
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- name: F1
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type: f1
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value: 0.9110979228486646
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- name: Accuracy
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type: accuracy
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value: 0.9692018443081606
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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This model is a fine-tuned version of [layoutlmv3](https://huggingface.co/layoutlmv3) on the mp-02/cord-sroie dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1101
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- Precision: 0.9129
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- Recall: 0.9093
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- F1: 0.9111
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- Accuracy: 0.9692
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| No log | 0.7143 | 100 | 0.4587 | 0.5999 | 0.6098 | 0.6048 | 0.8921 |
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| No log | 1.4286 | 200 | 0.2729 | 0.8217 | 0.8299 | 0.8258 | 0.9428 |
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| No log | 2.1429 | 300 | 0.1556 | 0.9019 | 0.8998 | 0.9009 | 0.9678 |
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| No log | 2.8571 | 400 | 0.1274 | 0.8712 | 0.9372 | 0.9030 | 0.9652 |
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| 0.6303 | 3.5714 | 500 | 0.1101 | 0.9129 | 0.9093 | 0.9111 | 0.9692 |
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| 0.6303 | 4.2857 | 600 | 0.0870 | 0.9131 | 0.9510 | 0.9316 | 0.9761 |
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| 0.6303 | 5.0 | 700 | 0.0971 | 0.9089 | 0.9505 | 0.9292 | 0.9741 |
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| 0.6303 | 5.7143 | 800 | 0.1198 | 0.8859 | 0.9384 | 0.9114 | 0.9682 |
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| 0.6303 | 6.4286 | 900 | 0.1308 | 0.8930 | 0.9514 | 0.9213 | 0.9713 |
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### Framework versions
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all_results.json
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{
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"predict_accuracy": 0.
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"predict_f1": 0.
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"predict_loss": 0.
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"predict_precision": 0.
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"predict_recall": 0.
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"predict_runtime":
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"predict_samples_per_second": 7.
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"predict_steps_per_second": 0.
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}
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{
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"predict_accuracy": 0.9747414660931637,
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"predict_f1": 0.9250232126276695,
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"predict_loss": 0.10280822962522507,
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"predict_precision": 0.924165120593692,
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"predict_recall": 0.9258828996282528,
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"predict_runtime": 38.2729,
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"predict_samples_per_second": 7.133,
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"predict_steps_per_second": 0.914
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}
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predict_results.json
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{
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"predict_accuracy": 0.
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"predict_f1": 0.
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"predict_loss": 0.
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"predict_precision": 0.
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"predict_recall": 0.
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"predict_runtime":
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"predict_samples_per_second": 7.
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"predict_steps_per_second": 0.
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}
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{
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"predict_accuracy": 0.9747414660931637,
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"predict_f1": 0.9250232126276695,
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"predict_loss": 0.10280822962522507,
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"predict_precision": 0.924165120593692,
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"predict_recall": 0.9258828996282528,
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"predict_runtime": 38.2729,
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"predict_samples_per_second": 7.133,
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"predict_steps_per_second": 0.914
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}
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predictions.txt
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runs/Nov17_23-52-28_3855e7e7cdca/events.out.tfevents.1731887550.3855e7e7cdca.951.0
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