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--- |
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license: apache-2.0 |
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base_model: bert-large-cased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- universal_dependencies |
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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: bert-large-cased-upos |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: universal_dependencies |
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type: universal_dependencies |
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config: en_ewt |
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split: validation |
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args: en_ewt |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.8688031595250056 |
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- name: Recall |
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type: recall |
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value: 0.8557292884764056 |
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- name: F1 |
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type: f1 |
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value: 0.8617720995316154 |
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- name: Accuracy |
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type: accuracy |
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value: 0.8904395106479384 |
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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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# bert-large-cased-upos |
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This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the universal_dependencies dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4114 |
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- Precision: 0.8688 |
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- Recall: 0.8557 |
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- F1: 0.8618 |
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- Accuracy: 0.8904 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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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: 10 |
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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 | 1.0 | 438 | 0.5774 | 0.8348 | 0.7595 | 0.7893 | 0.8099 | |
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| No log | 2.0 | 876 | 0.4787 | 0.8114 | 0.7967 | 0.8000 | 0.8385 | |
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| No log | 3.0 | 1314 | 0.4345 | 0.8227 | 0.8302 | 0.8213 | 0.8601 | |
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| No log | 4.0 | 1752 | 0.4140 | 0.8257 | 0.8430 | 0.8304 | 0.8727 | |
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| No log | 5.0 | 2190 | 0.4211 | 0.8405 | 0.8525 | 0.8441 | 0.8787 | |
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| No log | 6.0 | 2628 | 0.4114 | 0.8688 | 0.8557 | 0.8618 | 0.8904 | |
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| No log | 7.0 | 3066 | 0.4582 | 0.8454 | 0.8572 | 0.8503 | 0.8911 | |
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| No log | 8.0 | 3504 | 0.4771 | 0.8447 | 0.8588 | 0.8508 | 0.8894 | |
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| No log | 9.0 | 3942 | 0.4799 | 0.8545 | 0.8626 | 0.8577 | 0.8918 | |
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| No log | 10.0 | 4380 | 0.4919 | 0.8539 | 0.8642 | 0.8579 | 0.8937 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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