---
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: 1.1031
- Precision: 0.8202
- Recall: 0.8158
- F1: 0.8134
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.3141        | 0.62  | 30   | 1.1728          | 0.4060    | 0.4868 | 0.4214 | 0.4868   |
| 0.8655        | 1.25  | 60   | 0.8567          | 0.7238    | 0.7237 | 0.7207 | 0.7237   |
| 0.6189        | 1.88  | 90   | 0.6433          | 0.7395    | 0.7368 | 0.7361 | 0.7368   |
| 0.4575        | 2.5   | 120  | 0.6314          | 0.7661    | 0.7632 | 0.7625 | 0.7632   |
| 0.3123        | 3.12  | 150  | 0.6091          | 0.7636    | 0.7632 | 0.7621 | 0.7632   |
| 0.215         | 3.75  | 180  | 0.6095          | 0.7769    | 0.7763 | 0.7758 | 0.7763   |
| 0.2901        | 4.38  | 210  | 0.6833          | 0.7409    | 0.7368 | 0.7367 | 0.7368   |
| 0.2169        | 5.0   | 240  | 0.6651          | 0.8354    | 0.8289 | 0.8285 | 0.8289   |
| 0.1721        | 5.62  | 270  | 0.6578          | 0.8530    | 0.8421 | 0.8416 | 0.8421   |
| 0.2103        | 6.25  | 300  | 0.7525          | 0.7506    | 0.75   | 0.7481 | 0.75     |
| 0.1021        | 6.88  | 330  | 0.6357          | 0.8725    | 0.8684 | 0.8681 | 0.8684   |
| 0.1115        | 7.5   | 360  | 1.0796          | 0.7510    | 0.75   | 0.7452 | 0.75     |
| 0.05          | 8.12  | 390  | 0.6933          | 0.8444    | 0.8289 | 0.8264 | 0.8289   |
| 0.0419        | 8.75  | 420  | 0.7248          | 0.8295    | 0.8158 | 0.8135 | 0.8158   |
| 0.0521        | 9.38  | 450  | 1.0193          | 0.7867    | 0.7895 | 0.7848 | 0.7895   |
| 0.0197        | 10.0  | 480  | 0.7878          | 0.7867    | 0.7895 | 0.7848 | 0.7895   |
| 0.0165        | 10.62 | 510  | 1.3815          | 0.7232    | 0.7105 | 0.6969 | 0.7105   |
| 0.0321        | 11.25 | 540  | 0.9198          | 0.7867    | 0.7895 | 0.7848 | 0.7895   |
| 0.0202        | 11.88 | 570  | 0.9919          | 0.8044    | 0.8026 | 0.7993 | 0.8026   |
| 0.0046        | 12.5  | 600  | 1.1230          | 0.7622    | 0.7632 | 0.7528 | 0.7632   |
| 0.0044        | 13.12 | 630  | 0.8484          | 0.8579    | 0.8553 | 0.8551 | 0.8553   |
| 0.0019        | 13.75 | 660  | 1.0979          | 0.7925    | 0.7895 | 0.7855 | 0.7895   |
| 0.0018        | 14.38 | 690  | 1.3561          | 0.7480    | 0.75   | 0.7438 | 0.75     |
| 0.0021        | 15.0  | 720  | 1.0228          | 0.8006    | 0.8026 | 0.7991 | 0.8026   |
| 0.0014        | 15.62 | 750  | 0.9298          | 0.8422    | 0.8421 | 0.8413 | 0.8421   |
| 0.0014        | 16.25 | 780  | 0.9537          | 0.8276    | 0.8289 | 0.8274 | 0.8289   |
| 0.0012        | 16.88 | 810  | 0.9708          | 0.8276    | 0.8289 | 0.8274 | 0.8289   |
| 0.0013        | 17.5  | 840  | 1.0009          | 0.8276    | 0.8289 | 0.8274 | 0.8289   |
| 0.0011        | 18.12 | 870  | 0.9999          | 0.8037    | 0.8026 | 0.7997 | 0.8026   |
| 0.0011        | 18.75 | 900  | 0.9871          | 0.8037    | 0.8026 | 0.7997 | 0.8026   |
| 0.001         | 19.38 | 930  | 0.9885          | 0.8276    | 0.8289 | 0.8274 | 0.8289   |
| 0.001         | 20.0  | 960  | 1.0078          | 0.8276    | 0.8289 | 0.8274 | 0.8289   |
| 0.0009        | 20.62 | 990  | 1.0204          | 0.8037    | 0.8026 | 0.7997 | 0.8026   |
| 0.0008        | 21.25 | 1020 | 1.0312          | 0.8037    | 0.8026 | 0.7997 | 0.8026   |
| 0.0008        | 21.88 | 1050 | 1.0438          | 0.8037    | 0.8026 | 0.7997 | 0.8026   |
| 0.0008        | 22.5  | 1080 | 1.0647          | 0.8037    | 0.8026 | 0.7997 | 0.8026   |
| 0.0008        | 23.12 | 1110 | 1.0633          | 0.8202    | 0.8158 | 0.8134 | 0.8158   |
| 0.0007        | 23.75 | 1140 | 1.0661          | 0.8202    | 0.8158 | 0.8134 | 0.8158   |
| 0.0008        | 24.38 | 1170 | 1.0871          | 0.8202    | 0.8158 | 0.8134 | 0.8158   |
| 0.0007        | 25.0  | 1200 | 1.0965          | 0.8202    | 0.8158 | 0.8134 | 0.8158   |
| 0.0007        | 25.62 | 1230 | 1.0893          | 0.8202    | 0.8158 | 0.8134 | 0.8158   |
| 0.0007        | 26.25 | 1260 | 1.0935          | 0.8202    | 0.8158 | 0.8134 | 0.8158   |
| 0.0007        | 26.88 | 1290 | 1.0942          | 0.8202    | 0.8158 | 0.8134 | 0.8158   |
| 0.0007        | 27.5  | 1320 | 1.0949          | 0.8202    | 0.8158 | 0.8134 | 0.8158   |
| 0.0007        | 28.12 | 1350 | 1.0937          | 0.8202    | 0.8158 | 0.8134 | 0.8158   |
| 0.0007        | 28.75 | 1380 | 1.0986          | 0.8202    | 0.8158 | 0.8134 | 0.8158   |
| 0.0007        | 29.38 | 1410 | 1.1030          | 0.8202    | 0.8158 | 0.8134 | 0.8158   |
| 0.0007        | 30.0  | 1440 | 1.1031          | 0.8202    | 0.8158 | 0.8134 | 0.8158   |


### Framework versions

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