---
base_model: google/mt5-small
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: massive_intent
  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. -->

[<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/halakoo-mohammadreza-sad-warrior/huggingface/runs/r891swua)
[<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/halakoo-mohammadreza-sad-warrior/huggingface/runs/r891swua)
[<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/halakoo-mohammadreza-sad-warrior/huggingface/runs/r891swua)
# massive_intent

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5894

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 9.6225        | 1.0   | 352  | 4.8167          |
| 3.975         | 2.0   | 704  | 2.0456          |
| 2.2634        | 3.0   | 1056 | 1.2890          |
| 1.8345        | 4.0   | 1408 | 0.9723          |
| 1.3851        | 5.0   | 1760 | 0.7764          |
| 1.3563        | 6.0   | 2112 | 0.6790          |
| 1.2511        | 7.0   | 2464 | 0.6373          |
| 1.2352        | 8.0   | 2816 | 0.6073          |
| 1.0519        | 9.0   | 3168 | 0.5942          |
| 1.0937        | 10.0  | 3520 | 0.5894          |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1