---
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