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license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: RoBERTa_token_classification_14_techs_basic_fixed
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. -->
# RoBERTa_token_classification_14_techs_basic_fixed
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2455
- Precision: 0.0809
- Recall: 0.0915
- F1: 0.0859
- Accuracy: 0.7099
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.1723 | 1.0 | 664 | 0.9597 | 0.1022 | 0.0284 | 0.0445 | 0.7705 |
| 1.0015 | 2.0 | 1328 | 0.9761 | 0.0908 | 0.0906 | 0.0907 | 0.7382 |
| 0.8659 | 3.0 | 1992 | 0.9519 | 0.1174 | 0.0808 | 0.0957 | 0.7578 |
| 0.6297 | 4.0 | 2656 | 1.0252 | 0.0920 | 0.0995 | 0.0956 | 0.7285 |
| 0.5716 | 5.0 | 3320 | 1.0423 | 0.1004 | 0.0879 | 0.0938 | 0.7402 |
| 0.5236 | 6.0 | 3984 | 1.0918 | 0.1041 | 0.0906 | 0.0969 | 0.7435 |
| 0.3943 | 7.0 | 4648 | 1.1581 | 0.0911 | 0.1030 | 0.0967 | 0.7060 |
| 0.3713 | 8.0 | 5312 | 1.2021 | 0.0902 | 0.0933 | 0.0917 | 0.7099 |
| 0.3525 | 9.0 | 5976 | 1.2281 | 0.0918 | 0.0986 | 0.0951 | 0.7148 |
| 0.296 | 10.0 | 6640 | 1.2455 | 0.0809 | 0.0915 | 0.0859 | 0.7099 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3
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