---
base_model: klue/roberta-small
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: logs_rand
  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. -->

# logs_rand

This model is a fine-tuned version of [klue/roberta-small](https://huggingface.co/klue/roberta-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0024
- Precision: 0.8742
- Recall: 0.8871
- F1: 0.8806
- Accuracy: 0.9992

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 57   | 0.0067          | 0.6685    | 0.6276 | 0.6474 | 0.9980   |
| No log        | 2.0   | 114  | 0.0035          | 0.8286    | 0.8312 | 0.8299 | 0.9989   |
| No log        | 3.0   | 171  | 0.0028          | 0.8690    | 0.8745 | 0.8717 | 0.9991   |
| No log        | 4.0   | 228  | 0.0026          | 0.8693    | 0.8840 | 0.8766 | 0.9992   |
| No log        | 5.0   | 285  | 0.0024          | 0.8742    | 0.8871 | 0.8806 | 0.9992   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.0.1
- Datasets 2.19.1
- Tokenizers 0.19.1