File size: 2,756 Bytes
c2c30e1 |
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 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 |
---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: roberta-base_fold_1_binary_v1
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_fold_1_binary_v1
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: 1.4984
- F1: 0.8339
## 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: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 1.0 | 288 | 0.3819 | 0.8117 |
| 0.4108 | 2.0 | 576 | 0.3696 | 0.8281 |
| 0.4108 | 3.0 | 864 | 0.4890 | 0.8343 |
| 0.2261 | 4.0 | 1152 | 0.7605 | 0.8298 |
| 0.2261 | 5.0 | 1440 | 0.7754 | 0.8307 |
| 0.1404 | 6.0 | 1728 | 0.7650 | 0.8174 |
| 0.0962 | 7.0 | 2016 | 0.8539 | 0.8315 |
| 0.0962 | 8.0 | 2304 | 1.0770 | 0.8263 |
| 0.0433 | 9.0 | 2592 | 1.1450 | 0.8292 |
| 0.0433 | 10.0 | 2880 | 1.1700 | 0.8205 |
| 0.0344 | 11.0 | 3168 | 1.2376 | 0.8241 |
| 0.0344 | 12.0 | 3456 | 1.2688 | 0.8329 |
| 0.0219 | 13.0 | 3744 | 1.3276 | 0.8283 |
| 0.0123 | 14.0 | 4032 | 1.2930 | 0.8320 |
| 0.0123 | 15.0 | 4320 | 1.4631 | 0.8266 |
| 0.0177 | 16.0 | 4608 | 1.4326 | 0.8270 |
| 0.0177 | 17.0 | 4896 | 1.4770 | 0.8334 |
| 0.0053 | 18.0 | 5184 | 1.5972 | 0.8214 |
| 0.0053 | 19.0 | 5472 | 1.5331 | 0.8327 |
| 0.0045 | 20.0 | 5760 | 1.5487 | 0.8359 |
| 0.0086 | 21.0 | 6048 | 1.4610 | 0.8315 |
| 0.0086 | 22.0 | 6336 | 1.4685 | 0.8353 |
| 0.0071 | 23.0 | 6624 | 1.4933 | 0.8358 |
| 0.0071 | 24.0 | 6912 | 1.4898 | 0.8310 |
| 0.0022 | 25.0 | 7200 | 1.4984 | 0.8339 |
### Framework versions
- Transformers 4.21.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
|