---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-gest-pred-seqeval-partialmatch
  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-gest-pred-seqeval-partialmatch

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: 0.6909
- Precision: 0.7952
- Recall: 0.7778
- F1: 0.7489
- Accuracy: 0.8458

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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 2.0269        | 1.0   | 147  | 1.2260          | 0.3446    | 0.3571 | 0.3404 | 0.6696   |
| 1.0422        | 2.0   | 294  | 0.8553          | 0.5596    | 0.5248 | 0.4885 | 0.7594   |
| 0.7198        | 3.0   | 441  | 0.7086          | 0.6623    | 0.6298 | 0.6110 | 0.8097   |
| 0.5231        | 4.0   | 588  | 0.6330          | 0.7415    | 0.7102 | 0.7061 | 0.8264   |
| 0.3947        | 5.0   | 735  | 0.6246          | 0.8023    | 0.7382 | 0.7446 | 0.8345   |
| 0.2866        | 6.0   | 882  | 0.6487          | 0.8263    | 0.7578 | 0.7496 | 0.8519   |
| 0.2338        | 7.0   | 1029 | 0.6662          | 0.7970    | 0.7608 | 0.7452 | 0.8465   |
| 0.1791        | 8.0   | 1176 | 0.6762          | 0.7923    | 0.7690 | 0.7432 | 0.8398   |
| 0.1495        | 9.0   | 1323 | 0.6496          | 0.8008    | 0.7946 | 0.7686 | 0.8552   |
| 0.1316        | 10.0  | 1470 | 0.6909          | 0.7952    | 0.7778 | 0.7489 | 0.8458   |


### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2