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---
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license: apache-2.0
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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-gest-pred-seqeval-partialmatch
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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-gest-pred-seqeval-partialmatch
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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: 0.8644
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- Precision: 0.8459
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- Recall: 0.8459
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- F1: 0.8459
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- Accuracy: 0.8349
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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: 16
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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: 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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| 1.8591 | 1.0 | 147 | 1.1031 | 0.7523 | 0.7523 | 0.7523 | 0.7172 |
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| 0.8967 | 2.0 | 294 | 0.8237 | 0.8036 | 0.8036 | 0.8036 | 0.7822 |
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| 0.5801 | 3.0 | 441 | 0.7738 | 0.8251 | 0.8251 | 0.8251 | 0.8088 |
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| 0.3924 | 4.0 | 588 | 0.7335 | 0.8316 | 0.8316 | 0.8316 | 0.8179 |
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| 0.2704 | 5.0 | 735 | 0.7467 | 0.8459 | 0.8459 | 0.8459 | 0.8342 |
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| 0.1802 | 6.0 | 882 | 0.7634 | 0.8420 | 0.8420 | 0.8420 | 0.8316 |
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| 0.1299 | 7.0 | 1029 | 0.8104 | 0.8270 | 0.8270 | 0.8270 | 0.8147 |
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| 0.0968 | 8.0 | 1176 | 0.8489 | 0.8375 | 0.8375 | 0.8375 | 0.8277 |
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| 0.0761 | 9.0 | 1323 | 0.8539 | 0.8459 | 0.8459 | 0.8459 | 0.8362 |
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| 0.0663 | 10.0 | 1470 | 0.8644 | 0.8459 | 0.8459 | 0.8459 | 0.8349 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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