---
base_model: martin-ha/toxic-comment-model
tags:
- generated_from_trainer
datasets:
- ag_news
metrics:
- accuracy
model-index:
- name: my_sequenceClassification_model
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: ag_news
      type: ag_news
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.49276315789473685
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# my_sequenceClassification_model

This model is a fine-tuned version of [martin-ha/toxic-comment-model](https://huggingface.co/martin-ha/toxic-comment-model) on the ag_news dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0299
- Accuracy: 0.4928

## 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: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0255        | 1.0   | 7500  | 0.0390          | 0.4909   |
| 0.0133        | 2.0   | 15000 | 0.0299          | 0.4928   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.13.3