---
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: 0.0128
- Precision: 0.9739
- Recall: 0.9708
- F1: 0.9723
- Accuracy: 0.9960

## 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  | 0.0548          | 0.8595    | 0.8533 | 0.8564 | 0.9777   |
| No log        | 2.0   | 438  | 0.0538          | 0.8705    | 0.8560 | 0.8632 | 0.9788   |
| 0.0699        | 3.0   | 657  | 0.0531          | 0.8735    | 0.8626 | 0.8680 | 0.9785   |
| 0.0699        | 4.0   | 876  | 0.0459          | 0.8872    | 0.8833 | 0.8853 | 0.9816   |
| 0.0635        | 5.0   | 1095 | 0.0437          | 0.8876    | 0.8934 | 0.8905 | 0.9829   |
| 0.0635        | 6.0   | 1314 | 0.0358          | 0.9093    | 0.9001 | 0.9047 | 0.9859   |
| 0.0567        | 7.0   | 1533 | 0.0333          | 0.9170    | 0.9111 | 0.9140 | 0.9874   |
| 0.0567        | 8.0   | 1752 | 0.0303          | 0.9364    | 0.9229 | 0.9296 | 0.9889   |
| 0.0567        | 9.0   | 1971 | 0.0263          | 0.9432    | 0.9285 | 0.9358 | 0.9905   |
| 0.0498        | 10.0  | 2190 | 0.0258          | 0.9320    | 0.9419 | 0.9369 | 0.9908   |
| 0.0498        | 11.0  | 2409 | 0.0237          | 0.9431    | 0.9445 | 0.9438 | 0.9916   |
| 0.0437        | 12.0  | 2628 | 0.0187          | 0.9646    | 0.9534 | 0.9590 | 0.9936   |
| 0.0437        | 13.0  | 2847 | 0.0179          | 0.9636    | 0.9609 | 0.9623 | 0.9945   |
| 0.0425        | 14.0  | 3066 | 0.0159          | 0.9671    | 0.9642 | 0.9657 | 0.9949   |
| 0.0425        | 15.0  | 3285 | 0.0146          | 0.9654    | 0.9648 | 0.9651 | 0.9952   |
| 0.0464        | 16.0  | 3504 | 0.0137          | 0.9691    | 0.9687 | 0.9689 | 0.9956   |
| 0.0464        | 17.0  | 3723 | 0.0135          | 0.9713    | 0.9695 | 0.9704 | 0.9957   |
| 0.0464        | 18.0  | 3942 | 0.0128          | 0.9739    | 0.9708 | 0.9723 | 0.9960   |


### Framework versions

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