---
base_model: klue/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: roberta-base-finetuned-tc
  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. -->

# roberta-base-finetuned-tc

This model is a fine-tuned version of [klue/roberta-base](https://huggingface.co/klue/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5510
- Accuracy: 0.8442
- F1: 0.8376
- Precision: 0.8466
- Recall: 0.8442

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 15   | 1.3600          | 0.5055   | 0.3395 | 0.2556    | 0.5055 |
| No log        | 2.0   | 30   | 0.9601          | 0.6712   | 0.5846 | 0.6041    | 0.6712 |
| No log        | 3.0   | 45   | 0.7381          | 0.7865   | 0.7621 | 0.7439    | 0.7865 |
| No log        | 4.0   | 60   | 0.6402          | 0.8172   | 0.7964 | 0.7793    | 0.8172 |
| No log        | 5.0   | 75   | 0.5886          | 0.8258   | 0.8074 | 0.8163    | 0.8258 |
| No log        | 6.0   | 90   | 0.5714          | 0.8344   | 0.8213 | 0.8280    | 0.8344 |
| No log        | 7.0   | 105  | 0.5618          | 0.8331   | 0.8233 | 0.8386    | 0.8331 |
| No log        | 8.0   | 120  | 0.5559          | 0.8380   | 0.8307 | 0.8428    | 0.8380 |
| No log        | 9.0   | 135  | 0.5510          | 0.8442   | 0.8376 | 0.8466    | 0.8442 |
| No log        | 10.0  | 150  | 0.5545          | 0.8429   | 0.8355 | 0.8454    | 0.8429 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2