---
license: apache-2.0
base_model: casual/nlp_til2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: nlp_til2
  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. -->

# nlp_til2

This model is a fine-tuned version of [casual/nlp_til2](https://huggingface.co/casual/nlp_til2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0041
- Precision: 0.9920
- Recall: 0.9923
- F1: 0.9921
- Accuracy: 0.9987

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 18

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 219  | 0.0286          | 0.9350    | 0.9281 | 0.9316 | 0.9896   |
| No log        | 2.0   | 438  | 0.0277          | 0.9439    | 0.9235 | 0.9336 | 0.9899   |
| 0.0365        | 3.0   | 657  | 0.0296          | 0.9127    | 0.9300 | 0.9213 | 0.9890   |
| 0.0365        | 4.0   | 876  | 0.0267          | 0.9232    | 0.9404 | 0.9317 | 0.9900   |
| 0.0332        | 5.0   | 1095 | 0.0205          | 0.9451    | 0.9599 | 0.9524 | 0.9929   |
| 0.0332        | 6.0   | 1314 | 0.0165          | 0.9725    | 0.9542 | 0.9633 | 0.9942   |
| 0.0293        | 7.0   | 1533 | 0.0145          | 0.9729    | 0.9579 | 0.9653 | 0.9946   |
| 0.0293        | 8.0   | 1752 | 0.0156          | 0.9577    | 0.9658 | 0.9617 | 0.9944   |
| 0.0293        | 9.0   | 1971 | 0.0111          | 0.9756    | 0.9737 | 0.9746 | 0.9961   |
| 0.0237        | 10.0  | 2190 | 0.0091          | 0.9773    | 0.9803 | 0.9788 | 0.9968   |
| 0.0237        | 11.0  | 2409 | 0.0088          | 0.9750    | 0.9803 | 0.9777 | 0.9968   |
| 0.0199        | 12.0  | 2628 | 0.0068          | 0.9888    | 0.9848 | 0.9868 | 0.9978   |
| 0.0199        | 13.0  | 2847 | 0.0070          | 0.9835    | 0.9847 | 0.9841 | 0.9977   |
| 0.0201        | 14.0  | 3066 | 0.0074          | 0.9834    | 0.9861 | 0.9848 | 0.9976   |
| 0.0201        | 15.0  | 3285 | 0.0051          | 0.9869    | 0.9889 | 0.9879 | 0.9983   |
| 0.0257        | 16.0  | 3504 | 0.0040          | 0.9921    | 0.9913 | 0.9917 | 0.9987   |
| 0.0257        | 17.0  | 3723 | 0.0045          | 0.9911    | 0.9922 | 0.9916 | 0.9987   |
| 0.0257        | 18.0  | 3942 | 0.0041          | 0.9920    | 0.9923 | 0.9921 | 0.9987   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1