File size: 1,683 Bytes
6cf3610 ef5cda6 6cf3610 ef5cda6 6cf3610 ef5cda6 6cf3610 ef5cda6 6cf3610 ef5cda6 6cf3610 ef5cda6 6cf3610 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 |
---
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: roberta-large-detect-dep-v2
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-large-detect-dep-v2
This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7719
- Accuracy: 0.691
- F1: 0.7625
## 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-06
- 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.6278 | 1.0 | 751 | 0.5546 | 0.763 | 0.8227 |
| 0.5472 | 2.0 | 1502 | 0.5449 | 0.743 | 0.8160 |
| 0.4787 | 3.0 | 2253 | 0.5744 | 0.72 | 0.7929 |
| 0.423 | 4.0 | 3004 | 0.7290 | 0.702 | 0.7799 |
| 0.3803 | 5.0 | 3755 | 0.7719 | 0.691 | 0.7625 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
|