sickcell69
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Training complete
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README.md
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---
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license: apache-2.0
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base_model: bert-base-cased
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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: bert-finetuned-ner
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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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# bert-finetuned-ner
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4022
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- Precision: 0.7421
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- Recall: 0.7951
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- F1: 0.7677
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- Accuracy: 0.8883
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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: 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: 3
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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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| 0.7548 | 1.0 | 680 | 0.4630 | 0.6857 | 0.7150 | 0.7000 | 0.8615 |
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| 0.4124 | 2.0 | 1360 | 0.4143 | 0.7299 | 0.7698 | 0.7493 | 0.8786 |
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| 0.2546 | 3.0 | 2040 | 0.4022 | 0.7421 | 0.7951 | 0.7677 | 0.8883 |
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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 2.20.0
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- Tokenizers 0.19.1
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runs/Jul29_07-29-07_9b0aa93e5939/events.out.tfevents.1722238148.9b0aa93e5939.759.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:7878b4c3eb52a78a20586d6482d4a216a9e5fd9e0716c8c50ee7cec598561d15
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size 8527
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