---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hat-tiny-cased-conversational-p2_1-grouped-128-v2
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/igorktech01/huggingface/runs/ai5bnj8e)
# hat-tiny-cased-conversational-p2_1-grouped-128-v2

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5454
- Accuracy: 0.5161

## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 30000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 3.3688        | 0.7422 | 7500  | 3.1865          | 0.4371   |
| 3.0558        | 1.4844 | 15000 | 2.9189          | 0.4672   |
| 2.8314        | 2.2266 | 22500 | 2.6859          | 0.4975   |
| 2.6241        | 2.9688 | 30000 | 2.5454          | 0.5161   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1