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---
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license: mit
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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: RoBERTa_token_classification_14_techs_basic_fixed
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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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# RoBERTa_token_classification_14_techs_basic_fixed
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2455
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- Precision: 0.0809
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- Recall: 0.0915
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- F1: 0.0859
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- Accuracy: 0.7099
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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: 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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| 1.1723 | 1.0 | 664 | 0.9597 | 0.1022 | 0.0284 | 0.0445 | 0.7705 |
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| 1.0015 | 2.0 | 1328 | 0.9761 | 0.0908 | 0.0906 | 0.0907 | 0.7382 |
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| 0.8659 | 3.0 | 1992 | 0.9519 | 0.1174 | 0.0808 | 0.0957 | 0.7578 |
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| 0.6297 | 4.0 | 2656 | 1.0252 | 0.0920 | 0.0995 | 0.0956 | 0.7285 |
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| 0.5716 | 5.0 | 3320 | 1.0423 | 0.1004 | 0.0879 | 0.0938 | 0.7402 |
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| 0.5236 | 6.0 | 3984 | 1.0918 | 0.1041 | 0.0906 | 0.0969 | 0.7435 |
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| 0.3943 | 7.0 | 4648 | 1.1581 | 0.0911 | 0.1030 | 0.0967 | 0.7060 |
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| 0.3713 | 8.0 | 5312 | 1.2021 | 0.0902 | 0.0933 | 0.0917 | 0.7099 |
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| 0.3525 | 9.0 | 5976 | 1.2281 | 0.0918 | 0.0986 | 0.0951 | 0.7148 |
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| 0.296 | 10.0 | 6640 | 1.2455 | 0.0809 | 0.0915 | 0.0859 | 0.7099 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.3.1+cu121
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- Datasets 2.20.0
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- Tokenizers 0.13.3
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