---
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: hs1024-nh128-nl24_custom
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: massive
      type: massive
      config: en-US
      split: validation
      args: en-US
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.05682582380632145
---

<!-- 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. -->

# hs1024-nh128-nl24_custom

This model is a fine-tuned version of [](https://huggingface.co/) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 3.7913
- Accuracy: 0.0568

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.865         | 0.35  | 500  | 3.7925          | 0.0516   |
| 3.8374        | 0.69  | 1000 | 3.8029          | 0.0644   |
| 3.8903        | 1.04  | 1500 | 3.8613          | 0.0271   |
| 3.8784        | 1.39  | 2000 | 3.8428          | 0.0403   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0