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license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_token_classification_14_techs
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# BERT_token_classification_14_techs
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0225
- Precision: 0.8752
- Recall: 0.9167
- F1: 0.8955
- Accuracy: 0.9927
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.5777 | 1.0 | 1907 | 0.4271 | 0.3517 | 0.0988 | 0.1543 | 0.8843 |
| 0.3951 | 2.0 | 3814 | 0.2512 | 0.4325 | 0.3259 | 0.3717 | 0.9227 |
| 0.2678 | 3.0 | 5721 | 0.1405 | 0.5783 | 0.5598 | 0.5689 | 0.9580 |
| 0.153 | 4.0 | 7628 | 0.0924 | 0.6640 | 0.6804 | 0.6721 | 0.9725 |
| 0.1129 | 5.0 | 9535 | 0.0717 | 0.7014 | 0.7462 | 0.7231 | 0.9773 |
| 0.0798 | 6.0 | 11442 | 0.0598 | 0.7699 | 0.8102 | 0.7895 | 0.9832 |
| 0.0637 | 7.0 | 13349 | 0.0405 | 0.8221 | 0.8484 | 0.8351 | 0.9883 |
| 0.0483 | 8.0 | 15256 | 0.0307 | 0.8259 | 0.8818 | 0.8529 | 0.9893 |
| 0.0375 | 9.0 | 17163 | 0.0244 | 0.8674 | 0.9123 | 0.8893 | 0.9919 |
| 0.0315 | 10.0 | 19070 | 0.0225 | 0.8752 | 0.9167 | 0.8955 | 0.9927 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3
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