---
license: apache-2.0
base_model: google/canine-s
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: sentence_splitter_final_v2
  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. -->

# sentence_splitter_final_v2

This model is a fine-tuned version of [google/canine-s](https://huggingface.co/google/canine-s) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Precision: 0.8
- Recall: 1.0
- F1: 0.8889
- Accuracy: 1.0000

## 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: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 95   | 0.0037          | 0.0690    | 0.5    | 0.1212 | 0.9988   |
| No log        | 2.0   | 190  | 0.0022          | 0.0909    | 1.0    | 0.1667 | 0.9993   |
| No log        | 3.0   | 285  | 0.0014          | 0.1333    | 1.0    | 0.2353 | 0.9995   |
| No log        | 4.0   | 380  | 0.0010          | 0.1905    | 1.0    | 0.32   | 0.9996   |
| No log        | 5.0   | 475  | 0.0008          | 0.25      | 1.0    | 0.4    | 0.9997   |
| 0.0096        | 6.0   | 570  | 0.0004          | 0.3636    | 1.0    | 0.5333 | 0.9998   |
| 0.0096        | 7.0   | 665  | 0.0004          | 0.2222    | 1.0    | 0.3636 | 0.9999   |
| 0.0096        | 8.0   | 760  | 0.0002          | 0.4       | 1.0    | 0.5714 | 0.9999   |
| 0.0096        | 9.0   | 855  | 0.0003          | 0.1905    | 1.0    | 0.32   | 0.9999   |
| 0.0096        | 10.0  | 950  | 0.0003          | 0.2105    | 1.0    | 0.3478 | 0.9999   |
| 0.0008        | 11.0  | 1045 | 0.0001          | 0.3333    | 1.0    | 0.5    | 1.0000   |
| 0.0008        | 12.0  | 1140 | 0.0001          | 0.5       | 1.0    | 0.6667 | 1.0000   |
| 0.0008        | 13.0  | 1235 | 0.0001          | 0.4444    | 1.0    | 0.6154 | 1.0000   |
| 0.0008        | 14.0  | 1330 | 0.0000          | 0.8       | 1.0    | 0.8889 | 1.0000   |
| 0.0008        | 15.0  | 1425 | 0.0000          | 0.6667    | 1.0    | 0.8    | 1.0000   |
| 0.0003        | 16.0  | 1520 | 0.0000          | 0.8       | 1.0    | 0.8889 | 1.0000   |
| 0.0003        | 17.0  | 1615 | 0.0000          | 0.8       | 1.0    | 0.8889 | 1.0000   |
| 0.0003        | 18.0  | 1710 | 0.0000          | 0.8       | 1.0    | 0.8889 | 1.0000   |
| 0.0003        | 19.0  | 1805 | 0.0000          | 0.8       | 1.0    | 0.8889 | 1.0000   |
| 0.0003        | 20.0  | 1900 | 0.0000          | 0.8       | 1.0    | 0.8889 | 1.0000   |
| 0.0003        | 21.0  | 1995 | 0.0000          | 0.8       | 1.0    | 0.8889 | 1.0000   |
| 0.0001        | 22.0  | 2090 | 0.0000          | 0.8       | 1.0    | 0.8889 | 1.0000   |
| 0.0001        | 23.0  | 2185 | 0.0000          | 0.8       | 1.0    | 0.8889 | 1.0000   |
| 0.0001        | 24.0  | 2280 | 0.0000          | 0.8       | 1.0    | 0.8889 | 1.0000   |
| 0.0001        | 25.0  | 2375 | 0.0000          | 0.8       | 1.0    | 0.8889 | 1.0000   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0