---
license: mit
base_model: prajjwal1/bert-tiny
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: tiny_bert_25_intents
  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. -->

# tiny_bert_25_intents

This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2718
- Accuracy: 0.9238
- F1: 0.9238

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 472  | 1.9552          | 0.6143   | 0.6143 |
| 2.6425        | 2.0   | 944  | 1.1750          | 0.7952   | 0.7952 |
| 1.5608        | 3.0   | 1416 | 0.7802          | 0.8667   | 0.8667 |
| 0.9473        | 4.0   | 1888 | 0.5623          | 0.8976   | 0.8976 |
| 0.6217        | 5.0   | 2360 | 0.4360          | 0.9167   | 0.9167 |
| 0.4313        | 6.0   | 2832 | 0.3584          | 0.9143   | 0.9143 |
| 0.3165        | 7.0   | 3304 | 0.3150          | 0.9238   | 0.9238 |
| 0.237         | 8.0   | 3776 | 0.3006          | 0.9214   | 0.9214 |
| 0.1674        | 9.0   | 4248 | 0.2799          | 0.9214   | 0.9214 |
| 0.1691        | 10.0  | 4720 | 0.2647          | 0.9238   | 0.9238 |
| 0.1263        | 11.0  | 5192 | 0.2742          | 0.9238   | 0.9238 |
| 0.1201        | 12.0  | 5664 | 0.2745          | 0.9214   | 0.9214 |
| 0.1132        | 13.0  | 6136 | 0.2641          | 0.9214   | 0.9214 |
| 0.1045        | 14.0  | 6608 | 0.2728          | 0.9238   | 0.9238 |
| 0.0918        | 15.0  | 7080 | 0.2718          | 0.9238   | 0.9238 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3