End of training
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README.md
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---
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license: mit
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base_model: nielsr/lilt-xlm-roberta-base
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: lilt-xlm-roberta-base-finetuned-DocLayNet-base_paragraphs_ml512-v1
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results: []
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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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should probably proofread and complete it, then remove this comment. -->
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# lilt-xlm-roberta-base-finetuned-DocLayNet-base_paragraphs_ml512-v1
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This model is a fine-tuned version of [nielsr/lilt-xlm-roberta-base](https://huggingface.co/nielsr/lilt-xlm-roberta-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4110
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- Precision: 0.8507
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- Recall: 0.8507
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- F1: 0.8507
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- Accuracy: 0.8507
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 8
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 1
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| No log | 0.0533 | 100 | 0.9209 | 0.6685 | 0.6685 | 0.6685 | 0.6685 |
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| No log | 0.1066 | 200 | 0.6489 | 0.8154 | 0.8154 | 0.8154 | 0.8154 |
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| No log | 0.1599 | 300 | 0.7198 | 0.7420 | 0.7420 | 0.7420 | 0.7420 |
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| No log | 0.2132 | 400 | 0.5487 | 0.7961 | 0.7961 | 0.7961 | 0.7961 |
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| 0.736 | 0.2665 | 500 | 0.4430 | 0.8669 | 0.8669 | 0.8669 | 0.8669 |
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| 0.736 | 0.3198 | 600 | 0.4406 | 0.8614 | 0.8614 | 0.8614 | 0.8614 |
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| 0.736 | 0.3731 | 700 | 0.4112 | 0.8651 | 0.8651 | 0.8651 | 0.8651 |
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| 0.736 | 0.4264 | 800 | 0.4101 | 0.8711 | 0.8711 | 0.8711 | 0.8711 |
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| 0.736 | 0.4797 | 900 | 0.4691 | 0.8398 | 0.8398 | 0.8398 | 0.8398 |
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| 0.4575 | 0.5330 | 1000 | 0.4894 | 0.8009 | 0.8009 | 0.8009 | 0.8009 |
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| 0.4575 | 0.5864 | 1100 | 0.4275 | 0.8553 | 0.8553 | 0.8553 | 0.8553 |
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| 0.4575 | 0.6397 | 1200 | 0.3614 | 0.8857 | 0.8857 | 0.8857 | 0.8857 |
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| 0.4575 | 0.6930 | 1300 | 0.4571 | 0.8432 | 0.8432 | 0.8432 | 0.8432 |
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| 0.4575 | 0.7463 | 1400 | 0.4478 | 0.8377 | 0.8377 | 0.8377 | 0.8377 |
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| 0.3718 | 0.7996 | 1500 | 0.4381 | 0.8324 | 0.8324 | 0.8324 | 0.8324 |
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| 0.3718 | 0.8529 | 1600 | 0.3267 | 0.8963 | 0.8963 | 0.8963 | 0.8963 |
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| 0.3718 | 0.9062 | 1700 | 0.3470 | 0.8890 | 0.8890 | 0.8890 | 0.8890 |
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| 0.3718 | 0.9595 | 1800 | 0.4110 | 0.8507 | 0.8507 | 0.8507 | 0.8507 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 1134332228
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version https://git-lfs.github.com/spec/v1
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size 1134332228
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runs/Jun03_04-23-17_880f70ab7feb/events.out.tfevents.1717388607.880f70ab7feb.13451.0
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version https://git-lfs.github.com/spec/v1
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size
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size 15139
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