---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: BLESSRelationTrain-1
  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. -->

# BLESSRelationTrain-1

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6904
- Accuracy: 0.6228
- Precision: 0.7030
- Recall: 0.4251
- F1: 0.5299

## 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: 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 0.8   | 100  | 0.6952          | 0.5      | 0.5       | 1.0    | 0.6667 |
| No log        | 1.6   | 200  | 0.6934          | 0.5      | 0.0       | 0.0    | 0.0    |
| No log        | 2.4   | 300  | 0.6944          | 0.5      | 0.5       | 1.0    | 0.6667 |
| No log        | 3.2   | 400  | 0.7126          | 0.5      | 0.0       | 0.0    | 0.0    |
| 0.7004        | 4.0   | 500  | 0.6979          | 0.5      | 0.5       | 1.0    | 0.6667 |
| 0.7004        | 4.8   | 600  | 0.6995          | 0.5      | 0.0       | 0.0    | 0.0    |
| 0.7004        | 5.6   | 700  | 0.6930          | 0.5      | 0.0       | 0.0    | 0.0    |
| 0.7004        | 6.4   | 800  | 0.6938          | 0.5      | 0.0       | 0.0    | 0.0    |
| 0.7004        | 7.2   | 900  | 0.6923          | 0.5      | 0.0       | 0.0    | 0.0    |
| 0.6958        | 8.0   | 1000 | 0.6904          | 0.6228   | 0.7030    | 0.4251 | 0.5299 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1