File size: 3,101 Bytes
da923d2 |
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 |
---
base_model: vinai/bertweet-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bertweet-base_3epoch10
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. -->
# bertweet-base_3epoch10
This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7005
- Accuracy: 0.7392
- F1: 0.4217
- Precision: 0.5789
- Recall: 0.3317
- Precision Sarcastic: 0.5789
- Recall Sarcastic: 0.3317
- F1 Sarcastic: 0.4217
## 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 | Accuracy | F1 | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:|
| No log | 1.0 | 174 | 1.3971 | 0.7493 | 0.4 | 0.6374 | 0.2915 | 0.6374 | 0.2915 | 0.4 |
| No log | 2.0 | 348 | 1.0371 | 0.7334 | 0.3854 | 0.5686 | 0.2915 | 0.5686 | 0.2915 | 0.3854 |
| 0.0617 | 3.0 | 522 | 1.6060 | 0.7147 | 0.4277 | 0.5034 | 0.3719 | 0.5034 | 0.3719 | 0.4277 |
| 0.0617 | 4.0 | 696 | 1.3603 | 0.7464 | 0.4172 | 0.6117 | 0.3166 | 0.6117 | 0.3166 | 0.4172 |
| 0.0617 | 5.0 | 870 | 1.5872 | 0.7478 | 0.4373 | 0.6071 | 0.3417 | 0.6071 | 0.3417 | 0.4373 |
| 0.032 | 6.0 | 1044 | 1.4206 | 0.7493 | 0.3916 | 0.6437 | 0.2814 | 0.6437 | 0.2814 | 0.3916 |
| 0.032 | 7.0 | 1218 | 1.4775 | 0.7507 | 0.4055 | 0.6413 | 0.2965 | 0.6413 | 0.2965 | 0.4055 |
| 0.032 | 8.0 | 1392 | 1.5835 | 0.7421 | 0.4389 | 0.5833 | 0.3518 | 0.5833 | 0.3518 | 0.4389 |
| 0.0125 | 9.0 | 1566 | 1.7009 | 0.7464 | 0.3846 | 0.6322 | 0.2764 | 0.6322 | 0.2764 | 0.3846 |
| 0.0125 | 10.0 | 1740 | 1.7005 | 0.7392 | 0.4217 | 0.5789 | 0.3317 | 0.5789 | 0.3317 | 0.4217 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|