---
license: apache-2.0
base_model: yhavinga/t5-small-24L-ccmatrix-multi
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: final_classifications
  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. -->

# final_classifications

This model is a fine-tuned version of [yhavinga/t5-small-24L-ccmatrix-multi](https://huggingface.co/yhavinga/t5-small-24L-ccmatrix-multi) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1005
- F1: {'f1': 0.9592760180995475}
- Precision: {'precision': 0.954954954954955}
- Recall: {'recall': 0.9636363636363636}

## 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: 0.0001
- 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: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1                         | Precision                         | Recall                         |
|:-------------:|:-----:|:----:|:---------------:|:--------------------------:|:---------------------------------:|:------------------------------:|
| No log        | 1.0   | 110  | 0.2362          | {'f1': 0.0}                | {'precision': 0.0}                | {'recall': 0.0}                |
| No log        | 2.0   | 220  | 0.1164          | {'f1': 0.9502262443438914} | {'precision': 0.9459459459459459} | {'recall': 0.9545454545454546} |
| No log        | 3.0   | 330  | 0.0832          | {'f1': 0.9596412556053813} | {'precision': 0.9469026548672567} | {'recall': 0.9727272727272728} |
| No log        | 4.0   | 440  | 0.0918          | {'f1': 0.9549549549549549} | {'precision': 0.9464285714285714} | {'recall': 0.9636363636363636} |
| 0.1554        | 5.0   | 550  | 0.0939          | {'f1': 0.9596412556053813} | {'precision': 0.9469026548672567} | {'recall': 0.9727272727272728} |
| 0.1554        | 6.0   | 660  | 0.1005          | {'f1': 0.9592760180995475} | {'precision': 0.954954954954955}  | {'recall': 0.9636363636363636} |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1