---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: canine_sent_0504
  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. -->

# canine_sent_0504

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: 0.0001
- Precision: 0.8919
- Recall: 0.9429
- F1: 0.9167
- 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 64   | 0.0037          | 0.1082    | 0.8286 | 0.1914 | 0.9988   |
| No log        | 2.0   | 128  | 0.0019          | 0.2013    | 0.8857 | 0.3280 | 0.9993   |
| No log        | 3.0   | 192  | 0.0015          | 0.3077    | 0.9143 | 0.4604 | 0.9994   |
| No log        | 4.0   | 256  | 0.0012          | 0.3855    | 0.9143 | 0.5424 | 0.9995   |
| No log        | 5.0   | 320  | 0.0011          | 0.2645    | 0.9143 | 0.4103 | 0.9995   |
| No log        | 6.0   | 384  | 0.0010          | 0.2406    | 0.9143 | 0.3810 | 0.9996   |
| No log        | 7.0   | 448  | 0.0008          | 0.2336    | 0.9143 | 0.3721 | 0.9996   |
| 0.008         | 8.0   | 512  | 0.0007          | 0.2623    | 0.9143 | 0.4076 | 0.9997   |
| 0.008         | 9.0   | 576  | 0.0006          | 0.3265    | 0.9143 | 0.4812 | 0.9998   |
| 0.008         | 10.0  | 640  | 0.0005          | 0.3137    | 0.9143 | 0.4672 | 0.9998   |
| 0.008         | 11.0  | 704  | 0.0004          | 0.4521    | 0.9429 | 0.6111 | 0.9999   |
| 0.008         | 12.0  | 768  | 0.0003          | 0.5       | 0.9429 | 0.6535 | 0.9999   |
| 0.008         | 13.0  | 832  | 0.0003          | 0.66      | 0.9429 | 0.7765 | 0.9999   |
| 0.008         | 14.0  | 896  | 0.0002          | 0.5238    | 0.9429 | 0.6735 | 0.9999   |
| 0.008         | 15.0  | 960  | 0.0002          | 0.7333    | 0.9429 | 0.8250 | 0.9999   |
| 0.0008        | 16.0  | 1024 | 0.0001          | 0.8684    | 0.9429 | 0.9041 | 1.0000   |
| 0.0008        | 17.0  | 1088 | 0.0001          | 0.8462    | 0.9429 | 0.8919 | 1.0000   |
| 0.0008        | 18.0  | 1152 | 0.0001          | 0.8684    | 0.9429 | 0.9041 | 1.0000   |
| 0.0008        | 19.0  | 1216 | 0.0001          | 0.8919    | 0.9429 | 0.9167 | 1.0000   |
| 0.0008        | 20.0  | 1280 | 0.0001          | 0.8919    | 0.9429 | 0.9167 | 1.0000   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2