---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: CONTEXT_one
  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. -->

# CONTEXT_one

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2483
- Precision: 0.8152
- Recall: 0.8158
- F1: 0.8141
- Accuracy: 0.8158

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.3127        | 0.62  | 30   | 1.1497          | 0.6818    | 0.5263 | 0.4785 | 0.5263   |
| 0.8414        | 1.25  | 60   | 0.8096          | 0.7479    | 0.75   | 0.7472 | 0.75     |
| 0.597         | 1.88  | 90   | 0.6579          | 0.7904    | 0.7895 | 0.7873 | 0.7895   |
| 0.4417        | 2.5   | 120  | 0.5761          | 0.8072    | 0.8026 | 0.8026 | 0.8026   |
| 0.3041        | 3.12  | 150  | 0.6691          | 0.7665    | 0.7632 | 0.7598 | 0.7632   |
| 0.2384        | 3.75  | 180  | 0.6736          | 0.7717    | 0.7632 | 0.7645 | 0.7632   |
| 0.28          | 4.38  | 210  | 0.7949          | 0.7602    | 0.7632 | 0.7574 | 0.7632   |
| 0.22          | 5.0   | 240  | 0.8305          | 0.7917    | 0.7895 | 0.7879 | 0.7895   |
| 0.1427        | 5.62  | 270  | 0.7339          | 0.8041    | 0.8026 | 0.8025 | 0.8026   |
| 0.1875        | 6.25  | 300  | 0.7198          | 0.8031    | 0.7895 | 0.7909 | 0.7895   |
| 0.1216        | 6.88  | 330  | 0.7462          | 0.8315    | 0.8289 | 0.8287 | 0.8289   |
| 0.0895        | 7.5   | 360  | 0.8646          | 0.8070    | 0.8026 | 0.8006 | 0.8026   |
| 0.0758        | 8.12  | 390  | 1.0129          | 0.7883    | 0.7632 | 0.7642 | 0.7632   |
| 0.0636        | 8.75  | 420  | 0.9161          | 0.7893    | 0.7895 | 0.7866 | 0.7895   |
| 0.0239        | 9.38  | 450  | 0.9354          | 0.7409    | 0.7368 | 0.7367 | 0.7368   |
| 0.0449        | 10.0  | 480  | 1.0156          | 0.7994    | 0.8026 | 0.7980 | 0.8026   |
| 0.0089        | 10.62 | 510  | 0.9735          | 0.8125    | 0.8158 | 0.8125 | 0.8158   |
| 0.0348        | 11.25 | 540  | 1.0077          | 0.7867    | 0.7895 | 0.7848 | 0.7895   |
| 0.0037        | 11.88 | 570  | 1.1631          | 0.7868    | 0.7895 | 0.7857 | 0.7895   |
| 0.0022        | 12.5  | 600  | 1.1037          | 0.7998    | 0.8026 | 0.7993 | 0.8026   |
| 0.026         | 13.12 | 630  | 1.0309          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0118        | 13.75 | 660  | 1.0360          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0125        | 14.38 | 690  | 1.2095          | 0.7867    | 0.7895 | 0.7848 | 0.7895   |
| 0.0158        | 15.0  | 720  | 1.0658          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0072        | 15.62 | 750  | 1.1267          | 0.7708    | 0.7763 | 0.7688 | 0.7763   |
| 0.0015        | 16.25 | 780  | 1.1247          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0018        | 16.88 | 810  | 1.1386          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0013        | 17.5  | 840  | 1.1468          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0011        | 18.12 | 870  | 1.1692          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0013        | 18.75 | 900  | 1.1734          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0011        | 19.38 | 930  | 1.1857          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.001         | 20.0  | 960  | 1.1890          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.001         | 20.62 | 990  | 1.1924          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0009        | 21.25 | 1020 | 1.2005          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0009        | 21.88 | 1050 | 1.2084          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0009        | 22.5  | 1080 | 1.2216          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0009        | 23.12 | 1110 | 1.2237          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0008        | 23.75 | 1140 | 1.2231          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0008        | 24.38 | 1170 | 1.2286          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0008        | 25.0  | 1200 | 1.2312          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0008        | 25.62 | 1230 | 1.2325          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0008        | 26.25 | 1260 | 1.2362          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0008        | 26.88 | 1290 | 1.2415          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0007        | 27.5  | 1320 | 1.2462          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0008        | 28.12 | 1350 | 1.2471          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0007        | 28.75 | 1380 | 1.2466          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0007        | 29.38 | 1410 | 1.2478          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |
| 0.0007        | 30.0  | 1440 | 1.2483          | 0.8152    | 0.8158 | 0.8141 | 0.8158   |


### Framework versions

- Transformers 4.37.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1