---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mtop
model-index:
- name: t5-small-pointer-mtop
  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. -->

# t5-small-pointer-mtop

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the mtop dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1064
- Exact Match: 0.7570

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 3000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Exact Match |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|
| 2.0944        | 6.65  | 200  | 0.6548          | 0.0027      |
| 0.5307        | 13.33 | 400  | 0.2456          | 0.2779      |
| 0.2388        | 19.98 | 600  | 0.1486          | 0.4559      |
| 0.1459        | 26.65 | 800  | 0.1190          | 0.5043      |
| 0.1011        | 33.33 | 1000 | 0.1117          | 0.5230      |
| 0.0774        | 39.98 | 1200 | 0.1084          | 0.5374      |
| 0.0598        | 46.65 | 1400 | 0.1064          | 0.5405      |
| 0.0478        | 53.33 | 1600 | 0.1147          | 0.5454      |
| 0.0397        | 59.98 | 1800 | 0.1139          | 0.5472      |
| 0.0337        | 66.65 | 2000 | 0.1179          | 0.5481      |
| 0.0286        | 73.33 | 2200 | 0.1243          | 0.5499      |
| 0.0251        | 79.98 | 2400 | 0.1259          | 0.5481      |
| 0.0218        | 86.65 | 2600 | 0.1276          | 0.5503      |
| 0.0197        | 93.33 | 2800 | 0.1309          | 0.5503      |
| 0.0184        | 99.98 | 3000 | 0.1317          | 0.5503      |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2