---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: CONTEXT_two
  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_two

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: 0.9806
- Precision: 0.6800
- Recall: 0.6711
- F1: 0.6715
- Accuracy: 0.6711

## 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: 1e-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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.3915        | 0.31  | 15   | 1.3670          | 0.4926    | 0.4211 | 0.3467 | 0.4211   |
| 1.3405        | 0.62  | 30   | 1.3368          | 0.6504    | 0.4737 | 0.4176 | 0.4737   |
| 1.3104        | 0.94  | 45   | 1.2744          | 0.6319    | 0.5526 | 0.5575 | 0.5526   |
| 1.2038        | 1.25  | 60   | 1.1973          | 0.6648    | 0.6053 | 0.6130 | 0.6053   |
| 1.1289        | 1.56  | 75   | 1.1413          | 0.6826    | 0.6842 | 0.6827 | 0.6842   |
| 1.0146        | 1.88  | 90   | 1.0708          | 0.6920    | 0.6316 | 0.6313 | 0.6316   |
| 0.9391        | 2.19  | 105  | 1.0283          | 0.6488    | 0.6184 | 0.6174 | 0.6184   |
| 0.9295        | 2.5   | 120  | 0.9971          | 0.7229    | 0.6974 | 0.7025 | 0.6974   |
| 0.8569        | 2.81  | 135  | 0.9806          | 0.6800    | 0.6711 | 0.6715 | 0.6711   |


### Framework versions

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