---
license: mit
base_model: BigTMiami/micro_base_help_tapt_pretrain_model
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: micro_base_help_class_tapt_seed_4
  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. -->

# micro_base_help_class_tapt_seed_4

This model is a fine-tuned version of [BigTMiami/micro_base_help_tapt_pretrain_model](https://huggingface.co/BigTMiami/micro_base_help_tapt_pretrain_model) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9585
- Accuracy: 0.847
- F1 Macro: 0.6633

## 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: 16
- eval_batch_size: 16
- seed: 4
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 0.3721        | 1.0   | 313  | 0.3594          | 0.8574   | 0.5072   |
| 0.3008        | 2.0   | 626  | 0.3596          | 0.8662   | 0.6247   |
| 0.248         | 3.0   | 939  | 0.3616          | 0.8516   | 0.6425   |
| 0.1696        | 4.0   | 1252 | 0.5631          | 0.8306   | 0.6510   |
| 0.1631        | 5.0   | 1565 | 0.7292          | 0.8436   | 0.6440   |
| 0.1096        | 6.0   | 1878 | 1.0237          | 0.8378   | 0.6614   |
| 0.0839        | 7.0   | 2191 | 0.8822          | 0.8532   | 0.6140   |
| 0.0652        | 8.0   | 2504 | 1.0052          | 0.8532   | 0.6344   |
| 0.0329        | 9.0   | 2817 | 1.1225          | 0.848    | 0.6417   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2