File size: 3,458 Bytes
37835c2 |
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 85 86 87 88 89 90 91 92 93 94 95 96 |
---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: edos-2023-baseline-roberta-base-label_sexist
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. -->
# edos-2023-baseline-roberta-base-label_sexist
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0182
- F1: 0.9951
## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.5623 | 0.29 | 100 | 0.4459 | 0.6857 |
| 0.4055 | 0.57 | 200 | 0.3119 | 0.8135 |
| 0.3455 | 0.86 | 300 | 0.2704 | 0.8430 |
| 0.3198 | 1.14 | 400 | 0.2431 | 0.8640 |
| 0.2817 | 1.43 | 500 | 0.2579 | 0.8650 |
| 0.2997 | 1.71 | 600 | 0.2089 | 0.8911 |
| 0.2784 | 2.0 | 700 | 0.2069 | 0.8818 |
| 0.2231 | 2.29 | 800 | 0.2233 | 0.8872 |
| 0.2261 | 2.57 | 900 | 0.1598 | 0.9215 |
| 0.238 | 2.86 | 1000 | 0.1524 | 0.9137 |
| 0.2014 | 3.14 | 1100 | 0.1155 | 0.9441 |
| 0.1669 | 3.43 | 1200 | 0.1203 | 0.9436 |
| 0.1691 | 3.71 | 1300 | 0.0957 | 0.9566 |
| 0.1787 | 4.0 | 1400 | 0.0763 | 0.9709 |
| 0.1277 | 4.29 | 1500 | 0.0696 | 0.9717 |
| 0.1359 | 4.57 | 1600 | 0.0654 | 0.9734 |
| 0.1138 | 4.86 | 1700 | 0.0542 | 0.9788 |
| 0.1057 | 5.14 | 1800 | 0.0587 | 0.9747 |
| 0.1055 | 5.43 | 1900 | 0.0420 | 0.9843 |
| 0.0908 | 5.71 | 2000 | 0.0386 | 0.9866 |
| 0.1094 | 6.0 | 2100 | 0.0328 | 0.9890 |
| 0.0845 | 6.29 | 2200 | 0.0320 | 0.9885 |
| 0.0697 | 6.57 | 2300 | 0.0322 | 0.9893 |
| 0.083 | 6.86 | 2400 | 0.0260 | 0.9912 |
| 0.0659 | 7.14 | 2500 | 0.0259 | 0.9923 |
| 0.0745 | 7.43 | 2600 | 0.0304 | 0.9900 |
| 0.0623 | 7.71 | 2700 | 0.0284 | 0.9912 |
| 0.0825 | 8.0 | 2800 | 0.0215 | 0.9933 |
| 0.0414 | 8.29 | 2900 | 0.0222 | 0.9939 |
| 0.0477 | 8.57 | 3000 | 0.0231 | 0.9940 |
| 0.0606 | 8.86 | 3100 | 0.0211 | 0.9937 |
| 0.0616 | 9.14 | 3200 | 0.0190 | 0.9947 |
| 0.0413 | 9.43 | 3300 | 0.0182 | 0.9950 |
| 0.0462 | 9.71 | 3400 | 0.0181 | 0.9949 |
| 0.0473 | 10.0 | 3500 | 0.0182 | 0.9951 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
|