---
library_name: transformers
license: apache-2.0
base_model: skt/A.X-Encoder-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: aha_sentence_classification
  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. -->

# aha_sentence_classification

This model is a fine-tuned version of [skt/A.X-Encoder-base](https://huggingface.co/skt/A.X-Encoder-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8454
- Accuracy: 0.6900
- F1 Micro: 0.6900
- F1 Macro: 0.6503
- Precision Macro: 0.6078
- Recall Macro: 0.7221

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 25

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy | F1 Micro | F1 Macro | Precision Macro | Recall Macro |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:--------:|:--------:|:---------------:|:------------:|
| 0.9702        | 0.5949 | 1000  | 1.1520          | 0.5590   | 0.5590   | 0.5444   | 0.5142          | 0.6791       |
| 0.7293        | 1.1898 | 2000  | 1.0469          | 0.5992   | 0.5992   | 0.5966   | 0.5599          | 0.7238       |
| 0.7779        | 1.7847 | 3000  | 0.9977          | 0.6278   | 0.6278   | 0.5964   | 0.5646          | 0.7274       |
| 0.5545        | 2.3795 | 4000  | 0.9847          | 0.6290   | 0.6290   | 0.6208   | 0.5849          | 0.7236       |
| 0.5692        | 2.9744 | 5000  | 0.8454          | 0.6900   | 0.6900   | 0.6503   | 0.6078          | 0.7221       |
| 0.3962        | 3.5693 | 6000  | 1.0074          | 0.6488   | 0.6488   | 0.6316   | 0.6093          | 0.7081       |
| 0.1624        | 4.1642 | 7000  | 1.1059          | 0.6732   | 0.6732   | 0.6533   | 0.6322          | 0.6930       |
| 0.1816        | 4.7591 | 8000  | 1.1277          | 0.6872   | 0.6872   | 0.6513   | 0.6429          | 0.6690       |
| 0.0934        | 5.3540 | 9000  | 1.4084          | 0.6882   | 0.6882   | 0.6468   | 0.6380          | 0.6649       |
| 0.0882        | 5.9488 | 10000 | 1.4941          | 0.6918   | 0.6918   | 0.6450   | 0.6428          | 0.6606       |


### Framework versions

- Transformers 4.56.1
- Pytorch 2.7.0+cu126
- Tokenizers 0.22.0